# coding: utf-8

# Copyright 2018 IBM All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
The IBM Watson&trade; Discovery Service is a cognitive search and content analytics engine
that you can add to applications to identify patterns, trends and actionable insights to
drive better decision-making. Securely unify structured and unstructured data with
pre-enriched content, and use a simplified query language to eliminate the need for manual
filtering of results.
"""

from __future__ import absolute_import

import json
from .common import get_sdk_headers
from ibm_cloud_sdk_core import BaseService
from ibm_cloud_sdk_core import datetime_to_string, string_to_datetime
from os.path import basename

##############################################################################
# Service
##############################################################################


class DiscoveryV1(BaseService):
    """The Discovery V1 service."""

    default_url = 'https://gateway.watsonplatform.net/discovery/api'

    def __init__(
            self,
            version,
            url=default_url,
            username=None,
            password=None,
            iam_apikey=None,
            iam_access_token=None,
            iam_url=None,
    ):
        """
        Construct a new client for the Discovery service.

        :param str version: The API version date to use with the service, in
               "YYYY-MM-DD" format. Whenever the API is changed in a backwards
               incompatible way, a new minor version of the API is released.
               The service uses the API version for the date you specify, or
               the most recent version before that date. Note that you should
               not programmatically specify the current date at runtime, in
               case the API has been updated since your application's release.
               Instead, specify a version date that is compatible with your
               application, and don't change it until your application is
               ready for a later version.

        :param str url: The base url to use when contacting the service (e.g.
               "https://gateway.watsonplatform.net/discovery/api/discovery/api").
               The base url may differ between IBM Cloud regions.

        :param str username: The username used to authenticate with the service.
               Username and password credentials are only required to run your
               application locally or outside of IBM Cloud. When running on
               IBM Cloud, the credentials will be automatically loaded from the
               `VCAP_SERVICES` environment variable.

        :param str password: The password used to authenticate with the service.
               Username and password credentials are only required to run your
               application locally or outside of IBM Cloud. When running on
               IBM Cloud, the credentials will be automatically loaded from the
               `VCAP_SERVICES` environment variable.

        :param str iam_apikey: An API key that can be used to request IAM tokens. If
               this API key is provided, the SDK will manage the token and handle the
               refreshing.

        :param str iam_access_token:  An IAM access token is fully managed by the application.
               Responsibility falls on the application to refresh the token, either before
               it expires or reactively upon receiving a 401 from the service as any requests
               made with an expired token will fail.

        :param str iam_url: An optional URL for the IAM service API. Defaults to
               'https://iam.cloud.ibm.com/identity/token'.
        """

        BaseService.__init__(
            self,
            vcap_services_name='discovery',
            url=url,
            username=username,
            password=password,
            iam_apikey=iam_apikey,
            iam_access_token=iam_access_token,
            iam_url=iam_url,
            use_vcap_services=True,
            display_name='Discovery')
        self.version = version

    #########################
    # Environments
    #########################

    def create_environment(self, name, description=None, size=None, **kwargs):
        """
        Create an environment.

        Creates a new environment for private data. An environment must be created before
        collections can be created.
        **Note**: You can create only one environment for private data per service
        instance. An attempt to create another environment results in an error.

        :param str name: Name that identifies the environment.
        :param str description: Description of the environment.
        :param str size: Size of the environment. In the Lite plan the default and only
        accepted value is `LT`, in all other plans the default is `S`.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if name is None:
            raise ValueError('name must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'create_environment')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {'name': name, 'description': description, 'size': size}

        url = '/v1/environments'
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def delete_environment(self, environment_id, **kwargs):
        """
        Delete environment.

        :param str environment_id: The ID of the environment.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'delete_environment')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_environment(self, environment_id, **kwargs):
        """
        Get environment info.

        :param str environment_id: The ID of the environment.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'get_environment')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def list_environments(self, name=None, **kwargs):
        """
        List environments.

        List existing environments for the service instance.

        :param str name: Show only the environment with the given name.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'list_environments')
        headers.update(sdk_headers)

        params = {'version': self.version, 'name': name}

        url = '/v1/environments'
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def list_fields(self, environment_id, collection_ids, **kwargs):
        """
        List fields across collections.

        Gets a list of the unique fields (and their types) stored in the indexes of the
        specified collections.

        :param str environment_id: The ID of the environment.
        :param list[str] collection_ids: A comma-separated list of collection IDs to be
        queried against.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_ids is None:
            raise ValueError('collection_ids must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'list_fields')
        headers.update(sdk_headers)

        params = {
            'version': self.version,
            'collection_ids': self._convert_list(collection_ids)
        }

        url = '/v1/environments/{0}/fields'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def update_environment(self,
                           environment_id,
                           name=None,
                           description=None,
                           size=None,
                           **kwargs):
        """
        Update an environment.

        Updates an environment. The environment's **name** and  **description** parameters
        can be changed. You must specify a **name** for the environment.

        :param str environment_id: The ID of the environment.
        :param str name: Name that identifies the environment.
        :param str description: Description of the environment.
        :param str size: Size that the environment should be increased to. Environment
        size cannot be modified when using a Lite plan. Environment size can only
        increased and not decreased.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'update_environment')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {'name': name, 'description': description, 'size': size}

        url = '/v1/environments/{0}'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='PUT',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    #########################
    # Configurations
    #########################

    def create_configuration(self,
                             environment_id,
                             name,
                             description=None,
                             conversions=None,
                             enrichments=None,
                             normalizations=None,
                             source=None,
                             **kwargs):
        """
        Add configuration.

        Creates a new configuration.
        If the input configuration contains the **configuration_id**, **created**, or
        **updated** properties, then they are ignored and overridden by the system, and an
        error is not returned so that the overridden fields do not need to be removed when
        copying a configuration.
        The configuration can contain unrecognized JSON fields. Any such fields are
        ignored and do not generate an error. This makes it easier to use newer
        configuration files with older versions of the API and the service. It also makes
        it possible for the tooling to add additional metadata and information to the
        configuration.

        :param str environment_id: The ID of the environment.
        :param str name: The name of the configuration.
        :param str description: The description of the configuration, if available.
        :param Conversions conversions: Document conversion settings.
        :param list[Enrichment] enrichments: An array of document enrichment settings for
        the configuration.
        :param list[NormalizationOperation] normalizations: Defines operations that can be
        used to transform the final output JSON into a normalized form. Operations are
        executed in the order that they appear in the array.
        :param Source source: Object containing source parameters for the configuration.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if name is None:
            raise ValueError('name must be provided')
        if conversions is not None:
            conversions = self._convert_model(conversions, Conversions)
        if enrichments is not None:
            enrichments = [
                self._convert_model(x, Enrichment) for x in enrichments
            ]
        if normalizations is not None:
            normalizations = [
                self._convert_model(x, NormalizationOperation)
                for x in normalizations
            ]
        if source is not None:
            source = self._convert_model(source, Source)

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'create_configuration')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'name': name,
            'description': description,
            'conversions': conversions,
            'enrichments': enrichments,
            'normalizations': normalizations,
            'source': source
        }

        url = '/v1/environments/{0}/configurations'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def delete_configuration(self, environment_id, configuration_id, **kwargs):
        """
        Delete a configuration.

        The deletion is performed unconditionally. A configuration deletion request
        succeeds even if the configuration is referenced by a collection or document
        ingestion. However, documents that have already been submitted for processing
        continue to use the deleted configuration. Documents are always processed with a
        snapshot of the configuration as it existed at the time the document was
        submitted.

        :param str environment_id: The ID of the environment.
        :param str configuration_id: The ID of the configuration.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if configuration_id is None:
            raise ValueError('configuration_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'delete_configuration')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/configurations/{1}'.format(
            *self._encode_path_vars(environment_id, configuration_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_configuration(self, environment_id, configuration_id, **kwargs):
        """
        Get configuration details.

        :param str environment_id: The ID of the environment.
        :param str configuration_id: The ID of the configuration.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if configuration_id is None:
            raise ValueError('configuration_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'get_configuration')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/configurations/{1}'.format(
            *self._encode_path_vars(environment_id, configuration_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def list_configurations(self, environment_id, name=None, **kwargs):
        """
        List configurations.

        Lists existing configurations for the service instance.

        :param str environment_id: The ID of the environment.
        :param str name: Find configurations with the given name.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'list_configurations')
        headers.update(sdk_headers)

        params = {'version': self.version, 'name': name}

        url = '/v1/environments/{0}/configurations'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def update_configuration(self,
                             environment_id,
                             configuration_id,
                             name,
                             description=None,
                             conversions=None,
                             enrichments=None,
                             normalizations=None,
                             source=None,
                             **kwargs):
        """
        Update a configuration.

        Replaces an existing configuration.
          * Completely replaces the original configuration.
          * The **configuration_id**, **updated**, and **created** fields are accepted in
        the request, but they are ignored, and an error is not generated. It is also
        acceptable for users to submit an updated configuration with none of the three
        properties.
          * Documents are processed with a snapshot of the configuration as it was at the
        time the document was submitted to be ingested. This means that already submitted
        documents will not see any updates made to the configuration.

        :param str environment_id: The ID of the environment.
        :param str configuration_id: The ID of the configuration.
        :param str name: The name of the configuration.
        :param str description: The description of the configuration, if available.
        :param Conversions conversions: Document conversion settings.
        :param list[Enrichment] enrichments: An array of document enrichment settings for
        the configuration.
        :param list[NormalizationOperation] normalizations: Defines operations that can be
        used to transform the final output JSON into a normalized form. Operations are
        executed in the order that they appear in the array.
        :param Source source: Object containing source parameters for the configuration.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if configuration_id is None:
            raise ValueError('configuration_id must be provided')
        if name is None:
            raise ValueError('name must be provided')
        if conversions is not None:
            conversions = self._convert_model(conversions, Conversions)
        if enrichments is not None:
            enrichments = [
                self._convert_model(x, Enrichment) for x in enrichments
            ]
        if normalizations is not None:
            normalizations = [
                self._convert_model(x, NormalizationOperation)
                for x in normalizations
            ]
        if source is not None:
            source = self._convert_model(source, Source)

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'update_configuration')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'name': name,
            'description': description,
            'conversions': conversions,
            'enrichments': enrichments,
            'normalizations': normalizations,
            'source': source
        }

        url = '/v1/environments/{0}/configurations/{1}'.format(
            *self._encode_path_vars(environment_id, configuration_id))
        response = self.request(
            method='PUT',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    #########################
    # Test your configuration on a document
    #########################

    def test_configuration_in_environment(self,
                                          environment_id,
                                          configuration=None,
                                          file=None,
                                          filename=None,
                                          file_content_type=None,
                                          metadata=None,
                                          step=None,
                                          configuration_id=None,
                                          **kwargs):
        """
        Test configuration.

        Runs a sample document through the default or your configuration and returns
        diagnostic information designed to help you understand how the document was
        processed. The document is not added to the index.

        :param str environment_id: The ID of the environment.
        :param str configuration: The configuration to use to process the document. If
        this part is provided, then the provided configuration is used to process the
        document. If the **configuration_id** is also provided (both are present at the
        same time), then request is rejected. The maximum supported configuration size is
        1 MB. Configuration parts larger than 1 MB are rejected.
        See the `GET /configurations/{configuration_id}` operation for an example
        configuration.
        :param file file: The content of the document to ingest. The maximum supported
        file size when adding a file to a collection is 50 megabytes, the maximum
        supported file size when testing a confiruration is 1 megabyte. Files larger than
        the supported size are rejected.
        :param str filename: The filename for file.
        :param str file_content_type: The content type of file.
        :param str metadata: If you're using the Data Crawler to upload your documents,
        you can test a document against the type of metadata that the Data Crawler might
        send. The maximum supported metadata file size is 1 MB. Metadata parts larger than
        1 MB are rejected.
        Example:  ``` {
          \"Creator\": \"Johnny Appleseed\",
          \"Subject\": \"Apples\"
        } ```.
        :param str step: Specify to only run the input document through the given step
        instead of running the input document through the entire ingestion workflow. Valid
        values are `convert`, `enrich`, and `normalize`.
        :param str configuration_id: The ID of the configuration to use to process the
        document. If the **configuration** form part is also provided (both are present at
        the same time), then the request will be rejected.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'test_configuration_in_environment')
        headers.update(sdk_headers)

        params = {
            'version': self.version,
            'step': step,
            'configuration_id': configuration_id
        }

        form_data = {}
        if configuration:
            form_data['configuration'] = (None, configuration, 'text/plain')
        if file:
            if not filename and hasattr(file, 'name'):
                filename = basename(file.name)
            if not filename:
                raise ValueError('filename must be provided')
            form_data['file'] = (filename, file, file_content_type or
                                 'application/octet-stream')
        if metadata:
            form_data['metadata'] = (None, metadata, 'text/plain')

        url = '/v1/environments/{0}/preview'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            files=form_data,
            accept_json=True)
        return response

    #########################
    # Collections
    #########################

    def create_collection(self,
                          environment_id,
                          name,
                          description=None,
                          configuration_id=None,
                          language=None,
                          **kwargs):
        """
        Create a collection.

        :param str environment_id: The ID of the environment.
        :param str name: The name of the collection to be created.
        :param str description: A description of the collection.
        :param str configuration_id: The ID of the configuration in which the collection
        is to be created.
        :param str language: The language of the documents stored in the collection, in
        the form of an ISO 639-1 language code.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if name is None:
            raise ValueError('name must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'create_collection')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'name': name,
            'description': description,
            'configuration_id': configuration_id,
            'language': language
        }

        url = '/v1/environments/{0}/collections'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def delete_collection(self, environment_id, collection_id, **kwargs):
        """
        Delete a collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'delete_collection')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_collection(self, environment_id, collection_id, **kwargs):
        """
        Get collection details.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'get_collection')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def list_collection_fields(self, environment_id, collection_id, **kwargs):
        """
        List collection fields.

        Gets a list of the unique fields (and their types) stored in the index.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'list_collection_fields')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/fields'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def list_collections(self, environment_id, name=None, **kwargs):
        """
        List collections.

        Lists existing collections for the service instance.

        :param str environment_id: The ID of the environment.
        :param str name: Find collections with the given name.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'list_collections')
        headers.update(sdk_headers)

        params = {'version': self.version, 'name': name}

        url = '/v1/environments/{0}/collections'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def update_collection(self,
                          environment_id,
                          collection_id,
                          name,
                          description=None,
                          configuration_id=None,
                          **kwargs):
        """
        Update a collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str name: The name of the collection.
        :param str description: A description of the collection.
        :param str configuration_id: The ID of the configuration in which the collection
        is to be updated.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'update_collection')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'name': name,
            'description': description,
            'configuration_id': configuration_id
        }

        url = '/v1/environments/{0}/collections/{1}'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='PUT',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    #########################
    # Query modifications
    #########################

    def create_expansions(self, environment_id, collection_id, expansions,
                          **kwargs):
        """
        Create or update expansion list.

        Create or replace the Expansion list for this collection. The maximum number of
        expanded terms per collection is `500`.
        The current expansion list is replaced with the uploaded content.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param list[Expansion] expansions: An array of query expansion definitions.
         Each object in the **expansions** array represents a term or set of terms that
        will be expanded into other terms. Each expansion object can be configured as
        bidirectional or unidirectional. Bidirectional means that all terms are expanded
        to all other terms in the object. Unidirectional means that a set list of terms
        can be expanded into a second list of terms.
         To create a bi-directional expansion specify an **expanded_terms** array. When
        found in a query, all items in the **expanded_terms** array are then expanded to
        the other items in the same array.
         To create a uni-directional expansion, specify both an array of **input_terms**
        and an array of **expanded_terms**. When items in the **input_terms** array are
        present in a query, they are expanded using the items listed in the
        **expanded_terms** array.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if expansions is None:
            raise ValueError('expansions must be provided')
        expansions = [self._convert_model(x, Expansion) for x in expansions]

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'create_expansions')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {'expansions': expansions}

        url = '/v1/environments/{0}/collections/{1}/expansions'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def create_stopword_list(self,
                             environment_id,
                             collection_id,
                             stopword_file,
                             stopword_filename=None,
                             **kwargs):
        """
        Create stopword list.

        Upload a custom stopword list to use with the specified collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param file stopword_file: The content of the stopword list to ingest.
        :param str stopword_filename: The filename for stopword_file.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if stopword_file is None:
            raise ValueError('stopword_file must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'create_stopword_list')
        headers.update(sdk_headers)

        params = {'version': self.version}

        form_data = {}
        if not stopword_filename and hasattr(stopword_file, 'name'):
            stopword_filename = basename(stopword_file.name)
        if not stopword_filename:
            raise ValueError('stopword_filename must be provided')
        form_data['stopword_file'] = (stopword_filename, stopword_file,
                                      'application/octet-stream')

        url = '/v1/environments/{0}/collections/{1}/word_lists/stopwords'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            files=form_data,
            accept_json=True)
        return response

    def create_tokenization_dictionary(self,
                                       environment_id,
                                       collection_id,
                                       tokenization_rules=None,
                                       **kwargs):
        """
        Create tokenization dictionary.

        Upload a custom tokenization dictionary to use with the specified collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param list[TokenDictRule] tokenization_rules: An array of tokenization rules.
        Each rule contains, the original `text` string, component `tokens`, any alternate
        character set `readings`, and which `part_of_speech` the text is from.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if tokenization_rules is not None:
            tokenization_rules = [
                self._convert_model(x, TokenDictRule)
                for x in tokenization_rules
            ]

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'create_tokenization_dictionary')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {'tokenization_rules': tokenization_rules}

        url = '/v1/environments/{0}/collections/{1}/word_lists/tokenization_dictionary'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def delete_expansions(self, environment_id, collection_id, **kwargs):
        """
        Delete the expansion list.

        Remove the expansion information for this collection. The expansion list must be
        deleted to disable query expansion for a collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'delete_expansions')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/expansions'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=False)
        return response

    def delete_stopword_list(self, environment_id, collection_id, **kwargs):
        """
        Delete a custom stopword list.

        Delete a custom stopword list from the collection. After a custom stopword list is
        deleted, the default list is used for the collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'delete_stopword_list')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/word_lists/stopwords'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=False)
        return response

    def delete_tokenization_dictionary(self, environment_id, collection_id,
                                       **kwargs):
        """
        Delete tokenization dictionary.

        Delete the tokenization dictionary from the collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'delete_tokenization_dictionary')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/word_lists/tokenization_dictionary'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=False)
        return response

    def get_stopword_list_status(self, environment_id, collection_id, **kwargs):
        """
        Get stopword list status.

        Returns the current status of the stopword list for the specified collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'get_stopword_list_status')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/word_lists/stopwords'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_tokenization_dictionary_status(self, environment_id, collection_id,
                                           **kwargs):
        """
        Get tokenization dictionary status.

        Returns the current status of the tokenization dictionary for the specified
        collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'get_tokenization_dictionary_status')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/word_lists/tokenization_dictionary'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def list_expansions(self, environment_id, collection_id, **kwargs):
        """
        Get the expansion list.

        Returns the current expansion list for the specified collection. If an expansion
        list is not specified, an object with empty expansion arrays is returned.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'list_expansions')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/expansions'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    #########################
    # Documents
    #########################

    def add_document(self,
                     environment_id,
                     collection_id,
                     file=None,
                     filename=None,
                     file_content_type=None,
                     metadata=None,
                     **kwargs):
        """
        Add a document.

        Add a document to a collection with optional metadata.
          * The **version** query parameter is still required.
          * Returns immediately after the system has accepted the document for processing.
          * The user must provide document content, metadata, or both. If the request is
        missing both document content and metadata, it is rejected.
          * The user can set the **Content-Type** parameter on the **file** part to
        indicate the media type of the document. If the **Content-Type** parameter is
        missing or is one of the generic media types (for example,
        `application/octet-stream`), then the service attempts to automatically detect the
        document's media type.
          * The following field names are reserved and will be filtered out if present
        after normalization: `id`, `score`, `highlight`, and any field with the prefix of:
        `_`, `+`, or `-`
          * Fields with empty name values after normalization are filtered out before
        indexing.
          * Fields containing the following characters after normalization are filtered
        out before indexing: `#` and `,`
         **Note:** Documents can be added with a specific **document_id** by using the
        **_/v1/environments/{environment_id}/collections/{collection_id}/documents**
        method.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param file file: The content of the document to ingest. The maximum supported
        file size when adding a file to a collection is 50 megabytes, the maximum
        supported file size when testing a confiruration is 1 megabyte. Files larger than
        the supported size are rejected.
        :param str filename: The filename for file.
        :param str file_content_type: The content type of file.
        :param str metadata: If you're using the Data Crawler to upload your documents,
        you can test a document against the type of metadata that the Data Crawler might
        send. The maximum supported metadata file size is 1 MB. Metadata parts larger than
        1 MB are rejected.
        Example:  ``` {
          \"Creator\": \"Johnny Appleseed\",
          \"Subject\": \"Apples\"
        } ```.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'add_document')
        headers.update(sdk_headers)

        params = {'version': self.version}

        form_data = {}
        if file:
            if not filename and hasattr(file, 'name'):
                filename = basename(file.name)
            if not filename:
                raise ValueError('filename must be provided')
            form_data['file'] = (filename, file, file_content_type or
                                 'application/octet-stream')
        if metadata:
            form_data['metadata'] = (None, metadata, 'text/plain')

        url = '/v1/environments/{0}/collections/{1}/documents'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            files=form_data,
            accept_json=True)
        return response

    def delete_document(self, environment_id, collection_id, document_id,
                        **kwargs):
        """
        Delete a document.

        If the given document ID is invalid, or if the document is not found, then the a
        success response is returned (HTTP status code `200`) with the status set to
        'deleted'.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str document_id: The ID of the document.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if document_id is None:
            raise ValueError('document_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'delete_document')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/documents/{2}'.format(
            *self._encode_path_vars(environment_id, collection_id, document_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_document_status(self, environment_id, collection_id, document_id,
                            **kwargs):
        """
        Get document details.

        Fetch status details about a submitted document. **Note:** this operation does not
        return the document itself. Instead, it returns only the document's processing
        status and any notices (warnings or errors) that were generated when the document
        was ingested. Use the query API to retrieve the actual document content.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str document_id: The ID of the document.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if document_id is None:
            raise ValueError('document_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'get_document_status')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/documents/{2}'.format(
            *self._encode_path_vars(environment_id, collection_id, document_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def update_document(self,
                        environment_id,
                        collection_id,
                        document_id,
                        file=None,
                        filename=None,
                        file_content_type=None,
                        metadata=None,
                        **kwargs):
        """
        Update a document.

        Replace an existing document or add a document with a specified **document_id**.
        Starts ingesting a document with optional metadata.
        **Note:** When uploading a new document with this method it automatically replaces
        any document stored with the same **document_id** if it exists.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str document_id: The ID of the document.
        :param file file: The content of the document to ingest. The maximum supported
        file size when adding a file to a collection is 50 megabytes, the maximum
        supported file size when testing a confiruration is 1 megabyte. Files larger than
        the supported size are rejected.
        :param str filename: The filename for file.
        :param str file_content_type: The content type of file.
        :param str metadata: If you're using the Data Crawler to upload your documents,
        you can test a document against the type of metadata that the Data Crawler might
        send. The maximum supported metadata file size is 1 MB. Metadata parts larger than
        1 MB are rejected.
        Example:  ``` {
          \"Creator\": \"Johnny Appleseed\",
          \"Subject\": \"Apples\"
        } ```.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if document_id is None:
            raise ValueError('document_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'update_document')
        headers.update(sdk_headers)

        params = {'version': self.version}

        form_data = {}
        if file:
            if not filename and hasattr(file, 'name'):
                filename = basename(file.name)
            if not filename:
                raise ValueError('filename must be provided')
            form_data['file'] = (filename, file, file_content_type or
                                 'application/octet-stream')
        if metadata:
            form_data['metadata'] = (None, metadata, 'text/plain')

        url = '/v1/environments/{0}/collections/{1}/documents/{2}'.format(
            *self._encode_path_vars(environment_id, collection_id, document_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            files=form_data,
            accept_json=True)
        return response

    #########################
    # Queries
    #########################

    def federated_query(self,
                        environment_id,
                        filter=None,
                        query=None,
                        natural_language_query=None,
                        passages=None,
                        aggregation=None,
                        count=None,
                        return_fields=None,
                        offset=None,
                        sort=None,
                        highlight=None,
                        passages_fields=None,
                        passages_count=None,
                        passages_characters=None,
                        deduplicate=None,
                        deduplicate_field=None,
                        collection_ids=None,
                        similar=None,
                        similar_document_ids=None,
                        similar_fields=None,
                        bias=None,
                        logging_opt_out=None,
                        **kwargs):
        """
        Long environment queries.

        Complex queries might be too long for a standard method query. By using this
        method, you can construct longer queries. However, these queries may take longer
        to complete than the standard method. For details, see the [Discovery service
        documentation](https://cloud.ibm.com/docs/services/discovery?topic=discovery-query-concepts#query-concepts).

        :param str environment_id: The ID of the environment.
        :param str filter: A cacheable query that excludes documents that don't mention
        the query content. Filter searches are better for metadata-type searches and for
        assessing the concepts in the data set.
        :param str query: A query search returns all documents in your data set with full
        enrichments and full text, but with the most relevant documents listed first. Use
        a query search when you want to find the most relevant search results. You cannot
        use **natural_language_query** and **query** at the same time.
        :param str natural_language_query: A natural language query that returns relevant
        documents by utilizing training data and natural language understanding. You
        cannot use **natural_language_query** and **query** at the same time.
        :param bool passages: A passages query that returns the most relevant passages
        from the results.
        :param str aggregation: An aggregation search that returns an exact answer by
        combining query search with filters. Useful for applications to build lists,
        tables, and time series. For a full list of possible aggregations, see the Query
        reference.
        :param int count: Number of results to return.
        :param str return_fields: A comma-separated list of the portion of the document
        hierarchy to return.
        :param int offset: The number of query results to skip at the beginning. For
        example, if the total number of results that are returned is 10 and the offset is
        8, it returns the last two results.
        :param str sort: A comma-separated list of fields in the document to sort on. You
        can optionally specify a sort direction by prefixing the field with `-` for
        descending or `+` for ascending. Ascending is the default sort direction if no
        prefix is specified. This parameter cannot be used in the same query as the
        **bias** parameter.
        :param bool highlight: When true, a highlight field is returned for each result
        which contains the fields which match the query with `<em></em>` tags around the
        matching query terms.
        :param str passages_fields: A comma-separated list of fields that passages are
        drawn from. If this parameter not specified, then all top-level fields are
        included.
        :param int passages_count: The maximum number of passages to return. The search
        returns fewer passages if the requested total is not found. The default is `10`.
        The maximum is `100`.
        :param int passages_characters: The approximate number of characters that any one
        passage will have.
        :param bool deduplicate: When `true`, and used with a Watson Discovery News
        collection, duplicate results (based on the contents of the **title** field) are
        removed. Duplicate comparison is limited to the current query only; **offset** is
        not considered. This parameter is currently Beta functionality.
        :param str deduplicate_field: When specified, duplicate results based on the field
        specified are removed from the returned results. Duplicate comparison is limited
        to the current query only, **offset** is not considered. This parameter is
        currently Beta functionality.
        :param str collection_ids: A comma-separated list of collection IDs to be queried
        against. Required when querying multiple collections, invalid when performing a
        single collection query.
        :param bool similar: When `true`, results are returned based on their similarity
        to the document IDs specified in the **similar.document_ids** parameter.
        :param str similar_document_ids: A comma-separated list of document IDs to find
        similar documents.
        **Tip:** Include the **natural_language_query** parameter to expand the scope of
        the document similarity search with the natural language query. Other query
        parameters, such as **filter** and **query**, are subsequently applied and reduce
        the scope.
        :param str similar_fields: A comma-separated list of field names that are used as
        a basis for comparison to identify similar documents. If not specified, the entire
        document is used for comparison.
        :param str bias: Field which the returned results will be biased against. The
        specified field must be either a **date** or **number** format. When a **date**
        type field is specified returned results are biased towards field values closer to
        the current date. When a **number** type field is specified, returned results are
        biased towards higher field values. This parameter cannot be used in the same
        query as the **sort** parameter.
        :param bool logging_opt_out: If `true`, queries are not stored in the Discovery
        **Logs** endpoint.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')

        headers = {'X-Watson-Logging-Opt-Out': logging_opt_out}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'federated_query')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'filter': filter,
            'query': query,
            'natural_language_query': natural_language_query,
            'passages': passages,
            'aggregation': aggregation,
            'count': count,
            'return': return_fields,
            'offset': offset,
            'sort': sort,
            'highlight': highlight,
            'passages.fields': passages_fields,
            'passages.count': passages_count,
            'passages.characters': passages_characters,
            'deduplicate': deduplicate,
            'deduplicate.field': deduplicate_field,
            'collection_ids': collection_ids,
            'similar': similar,
            'similar.document_ids': similar_document_ids,
            'similar.fields': similar_fields,
            'bias': bias
        }

        url = '/v1/environments/{0}/query'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def federated_query_notices(self,
                                environment_id,
                                collection_ids,
                                filter=None,
                                query=None,
                                natural_language_query=None,
                                aggregation=None,
                                count=None,
                                return_fields=None,
                                offset=None,
                                sort=None,
                                highlight=None,
                                deduplicate_field=None,
                                similar=None,
                                similar_document_ids=None,
                                similar_fields=None,
                                **kwargs):
        """
        Query multiple collection system notices.

        Queries for notices (errors or warnings) that might have been generated by the
        system. Notices are generated when ingesting documents and performing relevance
        training. See the [Discovery service
        documentation](https://cloud.ibm.com/docs/services/discovery?topic=discovery-query-concepts#query-concepts)
        for more details on the query language.

        :param str environment_id: The ID of the environment.
        :param list[str] collection_ids: A comma-separated list of collection IDs to be
        queried against.
        :param str filter: A cacheable query that excludes documents that don't mention
        the query content. Filter searches are better for metadata-type searches and for
        assessing the concepts in the data set.
        :param str query: A query search returns all documents in your data set with full
        enrichments and full text, but with the most relevant documents listed first. Use
        a query search when you want to find the most relevant search results. You cannot
        use **natural_language_query** and **query** at the same time.
        :param str natural_language_query: A natural language query that returns relevant
        documents by utilizing training data and natural language understanding. You
        cannot use **natural_language_query** and **query** at the same time.
        :param str aggregation: An aggregation search that returns an exact answer by
        combining query search with filters. Useful for applications to build lists,
        tables, and time series. For a full list of possible aggregations, see the Query
        reference.
        :param int count: Number of results to return. The maximum for the **count** and
        **offset** values together in any one query is **10000**.
        :param list[str] return_fields: A comma-separated list of the portion of the
        document hierarchy to return.
        :param int offset: The number of query results to skip at the beginning. For
        example, if the total number of results that are returned is 10 and the offset is
        8, it returns the last two results. The maximum for the **count** and **offset**
        values together in any one query is **10000**.
        :param list[str] sort: A comma-separated list of fields in the document to sort
        on. You can optionally specify a sort direction by prefixing the field with `-`
        for descending or `+` for ascending. Ascending is the default sort direction if no
        prefix is specified.
        :param bool highlight: When true, a highlight field is returned for each result
        which contains the fields which match the query with `<em></em>` tags around the
        matching query terms.
        :param str deduplicate_field: When specified, duplicate results based on the field
        specified are removed from the returned results. Duplicate comparison is limited
        to the current query only, **offset** is not considered. This parameter is
        currently Beta functionality.
        :param bool similar: When `true`, results are returned based on their similarity
        to the document IDs specified in the **similar.document_ids** parameter.
        :param list[str] similar_document_ids: A comma-separated list of document IDs to
        find similar documents.
        **Tip:** Include the **natural_language_query** parameter to expand the scope of
        the document similarity search with the natural language query. Other query
        parameters, such as **filter** and **query**, are subsequently applied and reduce
        the scope.
        :param list[str] similar_fields: A comma-separated list of field names that are
        used as a basis for comparison to identify similar documents. If not specified,
        the entire document is used for comparison.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_ids is None:
            raise ValueError('collection_ids must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'federated_query_notices')
        headers.update(sdk_headers)

        params = {
            'version': self.version,
            'collection_ids': self._convert_list(collection_ids),
            'filter': filter,
            'query': query,
            'natural_language_query': natural_language_query,
            'aggregation': aggregation,
            'count': count,
            'return': self._convert_list(return_fields),
            'offset': offset,
            'sort': self._convert_list(sort),
            'highlight': highlight,
            'deduplicate.field': deduplicate_field,
            'similar': similar,
            'similar.document_ids': self._convert_list(similar_document_ids),
            'similar.fields': self._convert_list(similar_fields)
        }

        url = '/v1/environments/{0}/notices'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def query(self,
              environment_id,
              collection_id,
              filter=None,
              query=None,
              natural_language_query=None,
              passages=None,
              aggregation=None,
              count=None,
              return_fields=None,
              offset=None,
              sort=None,
              highlight=None,
              passages_fields=None,
              passages_count=None,
              passages_characters=None,
              deduplicate=None,
              deduplicate_field=None,
              collection_ids=None,
              similar=None,
              similar_document_ids=None,
              similar_fields=None,
              bias=None,
              logging_opt_out=None,
              **kwargs):
        """
        Long collection queries.

        Complex queries might be too long for a standard method query. By using this
        method, you can construct longer queries. However, these queries may take longer
        to complete than the standard method. For details, see the [Discovery service
        documentation](https://cloud.ibm.com/docs/services/discovery?topic=discovery-query-concepts#query-concepts).

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str filter: A cacheable query that excludes documents that don't mention
        the query content. Filter searches are better for metadata-type searches and for
        assessing the concepts in the data set.
        :param str query: A query search returns all documents in your data set with full
        enrichments and full text, but with the most relevant documents listed first. Use
        a query search when you want to find the most relevant search results. You cannot
        use **natural_language_query** and **query** at the same time.
        :param str natural_language_query: A natural language query that returns relevant
        documents by utilizing training data and natural language understanding. You
        cannot use **natural_language_query** and **query** at the same time.
        :param bool passages: A passages query that returns the most relevant passages
        from the results.
        :param str aggregation: An aggregation search that returns an exact answer by
        combining query search with filters. Useful for applications to build lists,
        tables, and time series. For a full list of possible aggregations, see the Query
        reference.
        :param int count: Number of results to return.
        :param str return_fields: A comma-separated list of the portion of the document
        hierarchy to return.
        :param int offset: The number of query results to skip at the beginning. For
        example, if the total number of results that are returned is 10 and the offset is
        8, it returns the last two results.
        :param str sort: A comma-separated list of fields in the document to sort on. You
        can optionally specify a sort direction by prefixing the field with `-` for
        descending or `+` for ascending. Ascending is the default sort direction if no
        prefix is specified. This parameter cannot be used in the same query as the
        **bias** parameter.
        :param bool highlight: When true, a highlight field is returned for each result
        which contains the fields which match the query with `<em></em>` tags around the
        matching query terms.
        :param str passages_fields: A comma-separated list of fields that passages are
        drawn from. If this parameter not specified, then all top-level fields are
        included.
        :param int passages_count: The maximum number of passages to return. The search
        returns fewer passages if the requested total is not found. The default is `10`.
        The maximum is `100`.
        :param int passages_characters: The approximate number of characters that any one
        passage will have.
        :param bool deduplicate: When `true`, and used with a Watson Discovery News
        collection, duplicate results (based on the contents of the **title** field) are
        removed. Duplicate comparison is limited to the current query only; **offset** is
        not considered. This parameter is currently Beta functionality.
        :param str deduplicate_field: When specified, duplicate results based on the field
        specified are removed from the returned results. Duplicate comparison is limited
        to the current query only, **offset** is not considered. This parameter is
        currently Beta functionality.
        :param str collection_ids: A comma-separated list of collection IDs to be queried
        against. Required when querying multiple collections, invalid when performing a
        single collection query.
        :param bool similar: When `true`, results are returned based on their similarity
        to the document IDs specified in the **similar.document_ids** parameter.
        :param str similar_document_ids: A comma-separated list of document IDs to find
        similar documents.
        **Tip:** Include the **natural_language_query** parameter to expand the scope of
        the document similarity search with the natural language query. Other query
        parameters, such as **filter** and **query**, are subsequently applied and reduce
        the scope.
        :param str similar_fields: A comma-separated list of field names that are used as
        a basis for comparison to identify similar documents. If not specified, the entire
        document is used for comparison.
        :param str bias: Field which the returned results will be biased against. The
        specified field must be either a **date** or **number** format. When a **date**
        type field is specified returned results are biased towards field values closer to
        the current date. When a **number** type field is specified, returned results are
        biased towards higher field values. This parameter cannot be used in the same
        query as the **sort** parameter.
        :param bool logging_opt_out: If `true`, queries are not stored in the Discovery
        **Logs** endpoint.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {'X-Watson-Logging-Opt-Out': logging_opt_out}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'query')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'filter': filter,
            'query': query,
            'natural_language_query': natural_language_query,
            'passages': passages,
            'aggregation': aggregation,
            'count': count,
            'return': return_fields,
            'offset': offset,
            'sort': sort,
            'highlight': highlight,
            'passages.fields': passages_fields,
            'passages.count': passages_count,
            'passages.characters': passages_characters,
            'deduplicate': deduplicate,
            'deduplicate.field': deduplicate_field,
            'collection_ids': collection_ids,
            'similar': similar,
            'similar.document_ids': similar_document_ids,
            'similar.fields': similar_fields,
            'bias': bias
        }

        url = '/v1/environments/{0}/collections/{1}/query'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def query_entities(self,
                       environment_id,
                       collection_id,
                       feature=None,
                       entity=None,
                       context=None,
                       count=None,
                       evidence_count=None,
                       **kwargs):
        """
        Knowledge Graph entity query.

        See the [Knowledge Graph
        documentation](https://cloud.ibm.com/docs/services/discovery?topic=discovery-kg#kg)
        for more details.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str feature: The entity query feature to perform. Supported features are
        `disambiguate` and `similar_entities`.
        :param QueryEntitiesEntity entity: A text string that appears within the entity
        text field.
        :param QueryEntitiesContext context: Entity text to provide context for the
        queried entity and rank based on that association. For example, if you wanted to
        query the city of London in England your query would look for `London` with the
        context of `England`.
        :param int count: The number of results to return. The default is `10`. The
        maximum is `1000`.
        :param int evidence_count: The number of evidence items to return for each result.
        The default is `0`. The maximum number of evidence items per query is 10,000.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if entity is not None:
            entity = self._convert_model(entity, QueryEntitiesEntity)
        if context is not None:
            context = self._convert_model(context, QueryEntitiesContext)

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'query_entities')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'feature': feature,
            'entity': entity,
            'context': context,
            'count': count,
            'evidence_count': evidence_count
        }

        url = '/v1/environments/{0}/collections/{1}/query_entities'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def query_notices(self,
                      environment_id,
                      collection_id,
                      filter=None,
                      query=None,
                      natural_language_query=None,
                      passages=None,
                      aggregation=None,
                      count=None,
                      return_fields=None,
                      offset=None,
                      sort=None,
                      highlight=None,
                      passages_fields=None,
                      passages_count=None,
                      passages_characters=None,
                      deduplicate_field=None,
                      similar=None,
                      similar_document_ids=None,
                      similar_fields=None,
                      **kwargs):
        """
        Query system notices.

        Queries for notices (errors or warnings) that might have been generated by the
        system. Notices are generated when ingesting documents and performing relevance
        training. See the [Discovery service
        documentation](https://cloud.ibm.com/docs/services/discovery?topic=discovery-query-concepts#query-concepts)
        for more details on the query language.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str filter: A cacheable query that excludes documents that don't mention
        the query content. Filter searches are better for metadata-type searches and for
        assessing the concepts in the data set.
        :param str query: A query search returns all documents in your data set with full
        enrichments and full text, but with the most relevant documents listed first. Use
        a query search when you want to find the most relevant search results. You cannot
        use **natural_language_query** and **query** at the same time.
        :param str natural_language_query: A natural language query that returns relevant
        documents by utilizing training data and natural language understanding. You
        cannot use **natural_language_query** and **query** at the same time.
        :param bool passages: A passages query that returns the most relevant passages
        from the results.
        :param str aggregation: An aggregation search that returns an exact answer by
        combining query search with filters. Useful for applications to build lists,
        tables, and time series. For a full list of possible aggregations, see the Query
        reference.
        :param int count: Number of results to return. The maximum for the **count** and
        **offset** values together in any one query is **10000**.
        :param list[str] return_fields: A comma-separated list of the portion of the
        document hierarchy to return.
        :param int offset: The number of query results to skip at the beginning. For
        example, if the total number of results that are returned is 10 and the offset is
        8, it returns the last two results. The maximum for the **count** and **offset**
        values together in any one query is **10000**.
        :param list[str] sort: A comma-separated list of fields in the document to sort
        on. You can optionally specify a sort direction by prefixing the field with `-`
        for descending or `+` for ascending. Ascending is the default sort direction if no
        prefix is specified.
        :param bool highlight: When true, a highlight field is returned for each result
        which contains the fields which match the query with `<em></em>` tags around the
        matching query terms.
        :param list[str] passages_fields: A comma-separated list of fields that passages
        are drawn from. If this parameter not specified, then all top-level fields are
        included.
        :param int passages_count: The maximum number of passages to return. The search
        returns fewer passages if the requested total is not found.
        :param int passages_characters: The approximate number of characters that any one
        passage will have.
        :param str deduplicate_field: When specified, duplicate results based on the field
        specified are removed from the returned results. Duplicate comparison is limited
        to the current query only, **offset** is not considered. This parameter is
        currently Beta functionality.
        :param bool similar: When `true`, results are returned based on their similarity
        to the document IDs specified in the **similar.document_ids** parameter.
        :param list[str] similar_document_ids: A comma-separated list of document IDs to
        find similar documents.
        **Tip:** Include the **natural_language_query** parameter to expand the scope of
        the document similarity search with the natural language query. Other query
        parameters, such as **filter** and **query**, are subsequently applied and reduce
        the scope.
        :param list[str] similar_fields: A comma-separated list of field names that are
        used as a basis for comparison to identify similar documents. If not specified,
        the entire document is used for comparison.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'query_notices')
        headers.update(sdk_headers)

        params = {
            'version': self.version,
            'filter': filter,
            'query': query,
            'natural_language_query': natural_language_query,
            'passages': passages,
            'aggregation': aggregation,
            'count': count,
            'return': self._convert_list(return_fields),
            'offset': offset,
            'sort': self._convert_list(sort),
            'highlight': highlight,
            'passages.fields': self._convert_list(passages_fields),
            'passages.count': passages_count,
            'passages.characters': passages_characters,
            'deduplicate.field': deduplicate_field,
            'similar': similar,
            'similar.document_ids': self._convert_list(similar_document_ids),
            'similar.fields': self._convert_list(similar_fields)
        }

        url = '/v1/environments/{0}/collections/{1}/notices'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def query_relations(self,
                        environment_id,
                        collection_id,
                        entities=None,
                        context=None,
                        sort=None,
                        filter=None,
                        count=None,
                        evidence_count=None,
                        **kwargs):
        """
        Knowledge Graph relationship query.

        See the [Knowledge Graph
        documentation](https://cloud.ibm.com/docs/services/discovery?topic=discovery-kg#kg)
        for more details.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param list[QueryRelationsEntity] entities: An array of entities to find
        relationships for.
        :param QueryEntitiesContext context: Entity text to provide context for the
        queried entity and rank based on that association. For example, if you wanted to
        query the city of London in England your query would look for `London` with the
        context of `England`.
        :param str sort: The sorting method for the relationships, can be `score` or
        `frequency`. `frequency` is the number of unique times each entity is identified.
        The default is `score`. This parameter cannot be used in the same query as the
        **bias** parameter.
        :param QueryRelationsFilter filter:
        :param int count: The number of results to return. The default is `10`. The
        maximum is `1000`.
        :param int evidence_count: The number of evidence items to return for each result.
        The default is `0`. The maximum number of evidence items per query is 10,000.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if entities is not None:
            entities = [
                self._convert_model(x, QueryRelationsEntity) for x in entities
            ]
        if context is not None:
            context = self._convert_model(context, QueryEntitiesContext)
        if filter is not None:
            filter = self._convert_model(filter, QueryRelationsFilter)

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'query_relations')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'entities': entities,
            'context': context,
            'sort': sort,
            'filter': filter,
            'count': count,
            'evidence_count': evidence_count
        }

        url = '/v1/environments/{0}/collections/{1}/query_relations'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    #########################
    # Training data
    #########################

    def add_training_data(self,
                          environment_id,
                          collection_id,
                          natural_language_query=None,
                          filter=None,
                          examples=None,
                          **kwargs):
        """
        Add query to training data.

        Adds a query to the training data for this collection. The query can contain a
        filter and natural language query.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str natural_language_query: The natural text query for the new training
        query.
        :param str filter: The filter used on the collection before the
        **natural_language_query** is applied.
        :param list[TrainingExample] examples: Array of training examples.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if examples is not None:
            examples = [
                self._convert_model(x, TrainingExample) for x in examples
            ]

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'add_training_data')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'natural_language_query': natural_language_query,
            'filter': filter,
            'examples': examples
        }

        url = '/v1/environments/{0}/collections/{1}/training_data'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def create_training_example(self,
                                environment_id,
                                collection_id,
                                query_id,
                                document_id=None,
                                cross_reference=None,
                                relevance=None,
                                **kwargs):
        """
        Add example to training data query.

        Adds a example to this training data query.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str query_id: The ID of the query used for training.
        :param str document_id: The document ID associated with this training example.
        :param str cross_reference: The cross reference associated with this training
        example.
        :param int relevance: The relevance of the training example.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if query_id is None:
            raise ValueError('query_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'create_training_example')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'document_id': document_id,
            'cross_reference': cross_reference,
            'relevance': relevance
        }

        url = '/v1/environments/{0}/collections/{1}/training_data/{2}/examples'.format(
            *self._encode_path_vars(environment_id, collection_id, query_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def delete_all_training_data(self, environment_id, collection_id, **kwargs):
        """
        Delete all training data.

        Deletes all training data from a collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'delete_all_training_data')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/training_data'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=False)
        return response

    def delete_training_data(self, environment_id, collection_id, query_id,
                             **kwargs):
        """
        Delete a training data query.

        Removes the training data query and all associated examples from the training data
        set.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str query_id: The ID of the query used for training.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if query_id is None:
            raise ValueError('query_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'delete_training_data')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/training_data/{2}'.format(
            *self._encode_path_vars(environment_id, collection_id, query_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=False)
        return response

    def delete_training_example(self, environment_id, collection_id, query_id,
                                example_id, **kwargs):
        """
        Delete example for training data query.

        Deletes the example document with the given ID from the training data query.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str query_id: The ID of the query used for training.
        :param str example_id: The ID of the document as it is indexed.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if query_id is None:
            raise ValueError('query_id must be provided')
        if example_id is None:
            raise ValueError('example_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'delete_training_example')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/training_data/{2}/examples/{3}'.format(
            *self._encode_path_vars(environment_id, collection_id, query_id,
                                    example_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=False)
        return response

    def get_training_data(self, environment_id, collection_id, query_id,
                          **kwargs):
        """
        Get details about a query.

        Gets details for a specific training data query, including the query string and
        all examples.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str query_id: The ID of the query used for training.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if query_id is None:
            raise ValueError('query_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'get_training_data')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/training_data/{2}'.format(
            *self._encode_path_vars(environment_id, collection_id, query_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_training_example(self, environment_id, collection_id, query_id,
                             example_id, **kwargs):
        """
        Get details for training data example.

        Gets the details for this training example.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str query_id: The ID of the query used for training.
        :param str example_id: The ID of the document as it is indexed.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if query_id is None:
            raise ValueError('query_id must be provided')
        if example_id is None:
            raise ValueError('example_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'get_training_example')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/training_data/{2}/examples/{3}'.format(
            *self._encode_path_vars(environment_id, collection_id, query_id,
                                    example_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def list_training_data(self, environment_id, collection_id, **kwargs):
        """
        List training data.

        Lists the training data for the specified collection.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'list_training_data')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/training_data'.format(
            *self._encode_path_vars(environment_id, collection_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def list_training_examples(self, environment_id, collection_id, query_id,
                               **kwargs):
        """
        List examples for a training data query.

        List all examples for this training data query.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str query_id: The ID of the query used for training.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if query_id is None:
            raise ValueError('query_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'list_training_examples')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/collections/{1}/training_data/{2}/examples'.format(
            *self._encode_path_vars(environment_id, collection_id, query_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def update_training_example(self,
                                environment_id,
                                collection_id,
                                query_id,
                                example_id,
                                cross_reference=None,
                                relevance=None,
                                **kwargs):
        """
        Change label or cross reference for example.

        Changes the label or cross reference query for this training data example.

        :param str environment_id: The ID of the environment.
        :param str collection_id: The ID of the collection.
        :param str query_id: The ID of the query used for training.
        :param str example_id: The ID of the document as it is indexed.
        :param str cross_reference: The example to add.
        :param int relevance: The relevance value for this example.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if collection_id is None:
            raise ValueError('collection_id must be provided')
        if query_id is None:
            raise ValueError('query_id must be provided')
        if example_id is None:
            raise ValueError('example_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'update_training_example')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {'cross_reference': cross_reference, 'relevance': relevance}

        url = '/v1/environments/{0}/collections/{1}/training_data/{2}/examples/{3}'.format(
            *self._encode_path_vars(environment_id, collection_id, query_id,
                                    example_id))
        response = self.request(
            method='PUT',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    #########################
    # User data
    #########################

    def delete_user_data(self, customer_id, **kwargs):
        """
        Delete labeled data.

        Deletes all data associated with a specified customer ID. The method has no effect
        if no data is associated with the customer ID.
        You associate a customer ID with data by passing the **X-Watson-Metadata** header
        with a request that passes data. For more information about personal data and
        customer IDs, see [Information
        security](https://cloud.ibm.com/docs/services/discovery?topic=discovery-information-security#information-security).

        :param str customer_id: The customer ID for which all data is to be deleted.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if customer_id is None:
            raise ValueError('customer_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'delete_user_data')
        headers.update(sdk_headers)

        params = {'version': self.version, 'customer_id': customer_id}

        url = '/v1/user_data'
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=False)
        return response

    #########################
    # Events and feedback
    #########################

    def create_event(self, type, data, **kwargs):
        """
        Create event.

        The **Events** API can be used to create log entries that are associated with
        specific queries. For example, you can record which documents in the results set
        were \"clicked\" by a user and when that click occured.

        :param str type: The event type to be created.
        :param EventData data: Query event data object.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if type is None:
            raise ValueError('type must be provided')
        if data is None:
            raise ValueError('data must be provided')
        data = self._convert_model(data, EventData)

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'create_event')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {'type': type, 'data': data}

        url = '/v1/events'
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def get_metrics_event_rate(self,
                               start_time=None,
                               end_time=None,
                               result_type=None,
                               **kwargs):
        """
        Percentage of queries with an associated event.

        The percentage of queries using the **natural_language_query** parameter that have
        a corresponding \"click\" event over a specified time window.  This metric
        requires having integrated event tracking in your application using the **Events**
        API.

        :param datetime start_time: Metric is computed from data recorded after this
        timestamp; must be in `YYYY-MM-DDThh:mm:ssZ` format.
        :param datetime end_time: Metric is computed from data recorded before this
        timestamp; must be in `YYYY-MM-DDThh:mm:ssZ` format.
        :param str result_type: The type of result to consider when calculating the
        metric.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'get_metrics_event_rate')
        headers.update(sdk_headers)

        params = {
            'version': self.version,
            'start_time': start_time,
            'end_time': end_time,
            'result_type': result_type
        }

        url = '/v1/metrics/event_rate'
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_metrics_query(self,
                          start_time=None,
                          end_time=None,
                          result_type=None,
                          **kwargs):
        """
        Number of queries over time.

        Total number of queries using the **natural_language_query** parameter over a
        specific time window.

        :param datetime start_time: Metric is computed from data recorded after this
        timestamp; must be in `YYYY-MM-DDThh:mm:ssZ` format.
        :param datetime end_time: Metric is computed from data recorded before this
        timestamp; must be in `YYYY-MM-DDThh:mm:ssZ` format.
        :param str result_type: The type of result to consider when calculating the
        metric.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'get_metrics_query')
        headers.update(sdk_headers)

        params = {
            'version': self.version,
            'start_time': start_time,
            'end_time': end_time,
            'result_type': result_type
        }

        url = '/v1/metrics/number_of_queries'
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_metrics_query_event(self,
                                start_time=None,
                                end_time=None,
                                result_type=None,
                                **kwargs):
        """
        Number of queries with an event over time.

        Total number of queries using the **natural_language_query** parameter that have a
        corresponding \"click\" event over a specified time window. This metric requires
        having integrated event tracking in your application using the **Events** API.

        :param datetime start_time: Metric is computed from data recorded after this
        timestamp; must be in `YYYY-MM-DDThh:mm:ssZ` format.
        :param datetime end_time: Metric is computed from data recorded before this
        timestamp; must be in `YYYY-MM-DDThh:mm:ssZ` format.
        :param str result_type: The type of result to consider when calculating the
        metric.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'get_metrics_query_event')
        headers.update(sdk_headers)

        params = {
            'version': self.version,
            'start_time': start_time,
            'end_time': end_time,
            'result_type': result_type
        }

        url = '/v1/metrics/number_of_queries_with_event'
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_metrics_query_no_results(self,
                                     start_time=None,
                                     end_time=None,
                                     result_type=None,
                                     **kwargs):
        """
        Number of queries with no search results over time.

        Total number of queries using the **natural_language_query** parameter that have
        no results returned over a specified time window.

        :param datetime start_time: Metric is computed from data recorded after this
        timestamp; must be in `YYYY-MM-DDThh:mm:ssZ` format.
        :param datetime end_time: Metric is computed from data recorded before this
        timestamp; must be in `YYYY-MM-DDThh:mm:ssZ` format.
        :param str result_type: The type of result to consider when calculating the
        metric.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'get_metrics_query_no_results')
        headers.update(sdk_headers)

        params = {
            'version': self.version,
            'start_time': start_time,
            'end_time': end_time,
            'result_type': result_type
        }

        url = '/v1/metrics/number_of_queries_with_no_search_results'
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_metrics_query_token_event(self, count=None, **kwargs):
        """
        Most frequent query tokens with an event.

        The most frequent query tokens parsed from the **natural_language_query**
        parameter and their corresponding \"click\" event rate within the recording period
        (queries and events are stored for 30 days). A query token is an individual word
        or unigram within the query string.

        :param int count: Number of results to return. The maximum for the **count** and
        **offset** values together in any one query is **10000**.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1',
                                      'get_metrics_query_token_event')
        headers.update(sdk_headers)

        params = {'version': self.version, 'count': count}

        url = '/v1/metrics/top_query_tokens_with_event_rate'
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def query_log(self,
                  filter=None,
                  query=None,
                  count=None,
                  offset=None,
                  sort=None,
                  **kwargs):
        """
        Search the query and event log.

        Searches the query and event log to find query sessions that match the specified
        criteria. Searching the **logs** endpoint uses the standard Discovery query syntax
        for the parameters that are supported.

        :param str filter: A cacheable query that excludes documents that don't mention
        the query content. Filter searches are better for metadata-type searches and for
        assessing the concepts in the data set.
        :param str query: A query search returns all documents in your data set with full
        enrichments and full text, but with the most relevant documents listed first. Use
        a query search when you want to find the most relevant search results. You cannot
        use **natural_language_query** and **query** at the same time.
        :param int count: Number of results to return. The maximum for the **count** and
        **offset** values together in any one query is **10000**.
        :param int offset: The number of query results to skip at the beginning. For
        example, if the total number of results that are returned is 10 and the offset is
        8, it returns the last two results. The maximum for the **count** and **offset**
        values together in any one query is **10000**.
        :param list[str] sort: A comma-separated list of fields in the document to sort
        on. You can optionally specify a sort direction by prefixing the field with `-`
        for descending or `+` for ascending. Ascending is the default sort direction if no
        prefix is specified.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'query_log')
        headers.update(sdk_headers)

        params = {
            'version': self.version,
            'filter': filter,
            'query': query,
            'count': count,
            'offset': offset,
            'sort': self._convert_list(sort)
        }

        url = '/v1/logs'
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    #########################
    # Credentials
    #########################

    def create_credentials(self,
                           environment_id,
                           source_type=None,
                           credential_details=None,
                           **kwargs):
        """
        Create credentials.

        Creates a set of credentials to connect to a remote source. Created credentials
        are used in a configuration to associate a collection with the remote source.
        **Note:** All credentials are sent over an encrypted connection and encrypted at
        rest.

        :param str environment_id: The ID of the environment.
        :param str source_type: The source that this credentials object connects to.
        -  `box` indicates the credentials are used to connect an instance of Enterprise
        Box.
        -  `salesforce` indicates the credentials are used to connect to Salesforce.
        -  `sharepoint` indicates the credentials are used to connect to Microsoft
        SharePoint Online.
        -  `web_crawl` indicates the credentials are used to perform a web crawl.
        =  `cloud_object_storage` indicates the credentials are used to connect to an IBM
        Cloud Object Store.
        :param CredentialDetails credential_details: Object containing details of the
        stored credentials.
        Obtain credentials for your source from the administrator of the source.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if credential_details is not None:
            credential_details = self._convert_model(credential_details,
                                                     CredentialDetails)

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'create_credentials')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'source_type': source_type,
            'credential_details': credential_details
        }

        url = '/v1/environments/{0}/credentials'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def delete_credentials(self, environment_id, credential_id, **kwargs):
        """
        Delete credentials.

        Deletes a set of stored credentials from your Discovery instance.

        :param str environment_id: The ID of the environment.
        :param str credential_id: The unique identifier for a set of source credentials.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if credential_id is None:
            raise ValueError('credential_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'delete_credentials')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/credentials/{1}'.format(
            *self._encode_path_vars(environment_id, credential_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_credentials(self, environment_id, credential_id, **kwargs):
        """
        View Credentials.

        Returns details about the specified credentials.
         **Note:** Secure credential information such as a password or SSH key is never
        returned and must be obtained from the source system.

        :param str environment_id: The ID of the environment.
        :param str credential_id: The unique identifier for a set of source credentials.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if credential_id is None:
            raise ValueError('credential_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'get_credentials')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/credentials/{1}'.format(
            *self._encode_path_vars(environment_id, credential_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def list_credentials(self, environment_id, **kwargs):
        """
        List credentials.

        List all the source credentials that have been created for this service instance.
         **Note:**  All credentials are sent over an encrypted connection and encrypted at
        rest.

        :param str environment_id: The ID of the environment.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'list_credentials')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/credentials'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def update_credentials(self,
                           environment_id,
                           credential_id,
                           source_type=None,
                           credential_details=None,
                           **kwargs):
        """
        Update credentials.

        Updates an existing set of source credentials.
        **Note:** All credentials are sent over an encrypted connection and encrypted at
        rest.

        :param str environment_id: The ID of the environment.
        :param str credential_id: The unique identifier for a set of source credentials.
        :param str source_type: The source that this credentials object connects to.
        -  `box` indicates the credentials are used to connect an instance of Enterprise
        Box.
        -  `salesforce` indicates the credentials are used to connect to Salesforce.
        -  `sharepoint` indicates the credentials are used to connect to Microsoft
        SharePoint Online.
        -  `web_crawl` indicates the credentials are used to perform a web crawl.
        =  `cloud_object_storage` indicates the credentials are used to connect to an IBM
        Cloud Object Store.
        :param CredentialDetails credential_details: Object containing details of the
        stored credentials.
        Obtain credentials for your source from the administrator of the source.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if credential_id is None:
            raise ValueError('credential_id must be provided')
        if credential_details is not None:
            credential_details = self._convert_model(credential_details,
                                                     CredentialDetails)

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'update_credentials')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {
            'source_type': source_type,
            'credential_details': credential_details
        }

        url = '/v1/environments/{0}/credentials/{1}'.format(
            *self._encode_path_vars(environment_id, credential_id))
        response = self.request(
            method='PUT',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    #########################
    # gatewayConfiguration
    #########################

    def create_gateway(self, environment_id, name=None, **kwargs):
        """
        Create Gateway.

        Create a gateway configuration to use with a remotely installed gateway.

        :param str environment_id: The ID of the environment.
        :param str name: User-defined name.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'create_gateway')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {'name': name}

        url = '/v1/environments/{0}/gateways'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response

    def delete_gateway(self, environment_id, gateway_id, **kwargs):
        """
        Delete Gateway.

        Delete the specified gateway configuration.

        :param str environment_id: The ID of the environment.
        :param str gateway_id: The requested gateway ID.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if gateway_id is None:
            raise ValueError('gateway_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'delete_gateway')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/gateways/{1}'.format(
            *self._encode_path_vars(environment_id, gateway_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def get_gateway(self, environment_id, gateway_id, **kwargs):
        """
        List Gateway Details.

        List information about the specified gateway.

        :param str environment_id: The ID of the environment.
        :param str gateway_id: The requested gateway ID.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')
        if gateway_id is None:
            raise ValueError('gateway_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'get_gateway')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/gateways/{1}'.format(
            *self._encode_path_vars(environment_id, gateway_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def list_gateways(self, environment_id, **kwargs):
        """
        List Gateways.

        List the currently configured gateways.

        :param str environment_id: The ID of the environment.
        :param dict headers: A `dict` containing the request headers
        :return: A `DetailedResponse` containing the result, headers and HTTP status code.
        :rtype: DetailedResponse
        """

        if environment_id is None:
            raise ValueError('environment_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('discovery', 'V1', 'list_gateways')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v1/environments/{0}/gateways'.format(
            *self._encode_path_vars(environment_id))
        response = self.request(
            method='GET',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response


##############################################################################
# Models
##############################################################################


class AggregationResult(object):
    """
    AggregationResult.

    :attr str key: (optional) Key that matched the aggregation type.
    :attr int matching_results: (optional) Number of matching results.
    :attr list[QueryAggregation] aggregations: (optional) Aggregations returned in the
    case of chained aggregations.
    """

    def __init__(self, key=None, matching_results=None, aggregations=None):
        """
        Initialize a AggregationResult object.

        :param str key: (optional) Key that matched the aggregation type.
        :param int matching_results: (optional) Number of matching results.
        :param list[QueryAggregation] aggregations: (optional) Aggregations returned in
        the case of chained aggregations.
        """
        self.key = key
        self.matching_results = matching_results
        self.aggregations = aggregations

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a AggregationResult object from a json dictionary."""
        args = {}
        if 'key' in _dict:
            args['key'] = _dict.get('key')
        if 'matching_results' in _dict:
            args['matching_results'] = _dict.get('matching_results')
        if 'aggregations' in _dict:
            args['aggregations'] = [
                QueryAggregation._from_dict(x)
                for x in (_dict.get('aggregations'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'key') and self.key is not None:
            _dict['key'] = self.key
        if hasattr(self,
                   'matching_results') and self.matching_results is not None:
            _dict['matching_results'] = self.matching_results
        if hasattr(self, 'aggregations') and self.aggregations is not None:
            _dict['aggregations'] = [x._to_dict() for x in self.aggregations]
        return _dict

    def __str__(self):
        """Return a `str` version of this AggregationResult object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Calculation(object):
    """
    Calculation.

    :attr str field: (optional) The field where the aggregation is located in the
    document.
    :attr float value: (optional) Value of the aggregation.
    """

    def __init__(self,
                 type=None,
                 results=None,
                 matching_results=None,
                 aggregations=None,
                 field=None,
                 value=None):
        """
        Initialize a Calculation object.

        :param str type: (optional) The type of aggregation command used. For example:
        term, filter, max, min, etc.
        :param list[AggregationResult] results: (optional) Array of aggregation results.
        :param int matching_results: (optional) Number of matching results.
        :param list[QueryAggregation] aggregations: (optional) Aggregations returned by
        the Discovery service.
        :param str field: (optional) The field where the aggregation is located in the
        document.
        :param float value: (optional) Value of the aggregation.
        """
        self.field = field
        self.value = value

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Calculation object from a json dictionary."""
        args = {}
        if 'field' in _dict:
            args['field'] = _dict.get('field')
        if 'value' in _dict:
            args['value'] = _dict.get('value')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'field') and self.field is not None:
            _dict['field'] = self.field
        if hasattr(self, 'value') and self.value is not None:
            _dict['value'] = self.value
        return _dict

    def __str__(self):
        """Return a `str` version of this Calculation object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Collection(object):
    """
    A collection for storing documents.

    :attr str collection_id: (optional) The unique identifier of the collection.
    :attr str name: (optional) The name of the collection.
    :attr str description: (optional) The description of the collection.
    :attr datetime created: (optional) The creation date of the collection in the format
    yyyy-MM-dd'T'HH:mmcon:ss.SSS'Z'.
    :attr datetime updated: (optional) The timestamp of when the collection was last
    updated in the format yyyy-MM-dd'T'HH:mm:ss.SSS'Z'.
    :attr str status: (optional) The status of the collection.
    :attr str configuration_id: (optional) The unique identifier of the collection's
    configuration.
    :attr str language: (optional) The language of the documents stored in the collection.
    Permitted values include `en` (English), `de` (German), and `es` (Spanish).
    :attr DocumentCounts document_counts: (optional)
    :attr CollectionDiskUsage disk_usage: (optional) Summary of the disk usage statistics
    for this collection.
    :attr TrainingStatus training_status: (optional)
    :attr SourceStatus source_crawl: (optional) Object containing source crawl status
    information.
    """

    def __init__(self,
                 collection_id=None,
                 name=None,
                 description=None,
                 created=None,
                 updated=None,
                 status=None,
                 configuration_id=None,
                 language=None,
                 document_counts=None,
                 disk_usage=None,
                 training_status=None,
                 source_crawl=None):
        """
        Initialize a Collection object.

        :param str collection_id: (optional) The unique identifier of the collection.
        :param str name: (optional) The name of the collection.
        :param str description: (optional) The description of the collection.
        :param datetime created: (optional) The creation date of the collection in the
        format yyyy-MM-dd'T'HH:mmcon:ss.SSS'Z'.
        :param datetime updated: (optional) The timestamp of when the collection was last
        updated in the format yyyy-MM-dd'T'HH:mm:ss.SSS'Z'.
        :param str status: (optional) The status of the collection.
        :param str configuration_id: (optional) The unique identifier of the collection's
        configuration.
        :param str language: (optional) The language of the documents stored in the
        collection. Permitted values include `en` (English), `de` (German), and `es`
        (Spanish).
        :param DocumentCounts document_counts: (optional)
        :param CollectionDiskUsage disk_usage: (optional) Summary of the disk usage
        statistics for this collection.
        :param TrainingStatus training_status: (optional)
        :param SourceStatus source_crawl: (optional) Object containing source crawl status
        information.
        """
        self.collection_id = collection_id
        self.name = name
        self.description = description
        self.created = created
        self.updated = updated
        self.status = status
        self.configuration_id = configuration_id
        self.language = language
        self.document_counts = document_counts
        self.disk_usage = disk_usage
        self.training_status = training_status
        self.source_crawl = source_crawl

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Collection object from a json dictionary."""
        args = {}
        if 'collection_id' in _dict:
            args['collection_id'] = _dict.get('collection_id')
        if 'name' in _dict:
            args['name'] = _dict.get('name')
        if 'description' in _dict:
            args['description'] = _dict.get('description')
        if 'created' in _dict:
            args['created'] = string_to_datetime(_dict.get('created'))
        if 'updated' in _dict:
            args['updated'] = string_to_datetime(_dict.get('updated'))
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        if 'configuration_id' in _dict:
            args['configuration_id'] = _dict.get('configuration_id')
        if 'language' in _dict:
            args['language'] = _dict.get('language')
        if 'document_counts' in _dict:
            args['document_counts'] = DocumentCounts._from_dict(
                _dict.get('document_counts'))
        if 'disk_usage' in _dict:
            args['disk_usage'] = CollectionDiskUsage._from_dict(
                _dict.get('disk_usage'))
        if 'training_status' in _dict:
            args['training_status'] = TrainingStatus._from_dict(
                _dict.get('training_status'))
        if 'source_crawl' in _dict:
            args['source_crawl'] = SourceStatus._from_dict(
                _dict.get('source_crawl'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'collection_id') and self.collection_id is not None:
            _dict['collection_id'] = self.collection_id
        if hasattr(self, 'name') and self.name is not None:
            _dict['name'] = self.name
        if hasattr(self, 'description') and self.description is not None:
            _dict['description'] = self.description
        if hasattr(self, 'created') and self.created is not None:
            _dict['created'] = datetime_to_string(self.created)
        if hasattr(self, 'updated') and self.updated is not None:
            _dict['updated'] = datetime_to_string(self.updated)
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        if hasattr(self,
                   'configuration_id') and self.configuration_id is not None:
            _dict['configuration_id'] = self.configuration_id
        if hasattr(self, 'language') and self.language is not None:
            _dict['language'] = self.language
        if hasattr(self,
                   'document_counts') and self.document_counts is not None:
            _dict['document_counts'] = self.document_counts._to_dict()
        if hasattr(self, 'disk_usage') and self.disk_usage is not None:
            _dict['disk_usage'] = self.disk_usage._to_dict()
        if hasattr(self,
                   'training_status') and self.training_status is not None:
            _dict['training_status'] = self.training_status._to_dict()
        if hasattr(self, 'source_crawl') and self.source_crawl is not None:
            _dict['source_crawl'] = self.source_crawl._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this Collection object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class CollectionDiskUsage(object):
    """
    Summary of the disk usage statistics for this collection.

    :attr int used_bytes: (optional) Number of bytes used by the collection.
    """

    def __init__(self, used_bytes=None):
        """
        Initialize a CollectionDiskUsage object.

        :param int used_bytes: (optional) Number of bytes used by the collection.
        """
        self.used_bytes = used_bytes

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a CollectionDiskUsage object from a json dictionary."""
        args = {}
        if 'used_bytes' in _dict:
            args['used_bytes'] = _dict.get('used_bytes')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'used_bytes') and self.used_bytes is not None:
            _dict['used_bytes'] = self.used_bytes
        return _dict

    def __str__(self):
        """Return a `str` version of this CollectionDiskUsage object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class CollectionUsage(object):
    """
    Summary of the collection usage in the environment.

    :attr int available: (optional) Number of active collections in the environment.
    :attr int maximum_allowed: (optional) Total number of collections allowed in the
    environment.
    """

    def __init__(self, available=None, maximum_allowed=None):
        """
        Initialize a CollectionUsage object.

        :param int available: (optional) Number of active collections in the environment.
        :param int maximum_allowed: (optional) Total number of collections allowed in the
        environment.
        """
        self.available = available
        self.maximum_allowed = maximum_allowed

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a CollectionUsage object from a json dictionary."""
        args = {}
        if 'available' in _dict:
            args['available'] = _dict.get('available')
        if 'maximum_allowed' in _dict:
            args['maximum_allowed'] = _dict.get('maximum_allowed')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'available') and self.available is not None:
            _dict['available'] = self.available
        if hasattr(self,
                   'maximum_allowed') and self.maximum_allowed is not None:
            _dict['maximum_allowed'] = self.maximum_allowed
        return _dict

    def __str__(self):
        """Return a `str` version of this CollectionUsage object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Configuration(object):
    """
    A custom configuration for the environment.

    :attr str configuration_id: (optional) The unique identifier of the configuration.
    :attr str name: The name of the configuration.
    :attr datetime created: (optional) The creation date of the configuration in the
    format yyyy-MM-dd'T'HH:mm:ss.SSS'Z'.
    :attr datetime updated: (optional) The timestamp of when the configuration was last
    updated in the format yyyy-MM-dd'T'HH:mm:ss.SSS'Z'.
    :attr str description: (optional) The description of the configuration, if available.
    :attr Conversions conversions: (optional) Document conversion settings.
    :attr list[Enrichment] enrichments: (optional) An array of document enrichment
    settings for the configuration.
    :attr list[NormalizationOperation] normalizations: (optional) Defines operations that
    can be used to transform the final output JSON into a normalized form. Operations are
    executed in the order that they appear in the array.
    :attr Source source: (optional) Object containing source parameters for the
    configuration.
    """

    def __init__(self,
                 name,
                 configuration_id=None,
                 created=None,
                 updated=None,
                 description=None,
                 conversions=None,
                 enrichments=None,
                 normalizations=None,
                 source=None):
        """
        Initialize a Configuration object.

        :param str name: The name of the configuration.
        :param str configuration_id: (optional) The unique identifier of the
        configuration.
        :param datetime created: (optional) The creation date of the configuration in the
        format yyyy-MM-dd'T'HH:mm:ss.SSS'Z'.
        :param datetime updated: (optional) The timestamp of when the configuration was
        last updated in the format yyyy-MM-dd'T'HH:mm:ss.SSS'Z'.
        :param str description: (optional) The description of the configuration, if
        available.
        :param Conversions conversions: (optional) Document conversion settings.
        :param list[Enrichment] enrichments: (optional) An array of document enrichment
        settings for the configuration.
        :param list[NormalizationOperation] normalizations: (optional) Defines operations
        that can be used to transform the final output JSON into a normalized form.
        Operations are executed in the order that they appear in the array.
        :param Source source: (optional) Object containing source parameters for the
        configuration.
        """
        self.configuration_id = configuration_id
        self.name = name
        self.created = created
        self.updated = updated
        self.description = description
        self.conversions = conversions
        self.enrichments = enrichments
        self.normalizations = normalizations
        self.source = source

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Configuration object from a json dictionary."""
        args = {}
        if 'configuration_id' in _dict:
            args['configuration_id'] = _dict.get('configuration_id')
        if 'name' in _dict:
            args['name'] = _dict.get('name')
        else:
            raise ValueError(
                'Required property \'name\' not present in Configuration JSON')
        if 'created' in _dict:
            args['created'] = string_to_datetime(_dict.get('created'))
        if 'updated' in _dict:
            args['updated'] = string_to_datetime(_dict.get('updated'))
        if 'description' in _dict:
            args['description'] = _dict.get('description')
        if 'conversions' in _dict:
            args['conversions'] = Conversions._from_dict(
                _dict.get('conversions'))
        if 'enrichments' in _dict:
            args['enrichments'] = [
                Enrichment._from_dict(x) for x in (_dict.get('enrichments'))
            ]
        if 'normalizations' in _dict:
            args['normalizations'] = [
                NormalizationOperation._from_dict(x)
                for x in (_dict.get('normalizations'))
            ]
        if 'source' in _dict:
            args['source'] = Source._from_dict(_dict.get('source'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self,
                   'configuration_id') and self.configuration_id is not None:
            _dict['configuration_id'] = self.configuration_id
        if hasattr(self, 'name') and self.name is not None:
            _dict['name'] = self.name
        if hasattr(self, 'created') and self.created is not None:
            _dict['created'] = datetime_to_string(self.created)
        if hasattr(self, 'updated') and self.updated is not None:
            _dict['updated'] = datetime_to_string(self.updated)
        if hasattr(self, 'description') and self.description is not None:
            _dict['description'] = self.description
        if hasattr(self, 'conversions') and self.conversions is not None:
            _dict['conversions'] = self.conversions._to_dict()
        if hasattr(self, 'enrichments') and self.enrichments is not None:
            _dict['enrichments'] = [x._to_dict() for x in self.enrichments]
        if hasattr(self, 'normalizations') and self.normalizations is not None:
            _dict['normalizations'] = [
                x._to_dict() for x in self.normalizations
            ]
        if hasattr(self, 'source') and self.source is not None:
            _dict['source'] = self.source._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this Configuration object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Conversions(object):
    """
    Document conversion settings.

    :attr PdfSettings pdf: (optional) A list of PDF conversion settings.
    :attr WordSettings word: (optional) A list of Word conversion settings.
    :attr HtmlSettings html: (optional) A list of HTML conversion settings.
    :attr SegmentSettings segment: (optional) A list of Document Segmentation settings.
    :attr list[NormalizationOperation] json_normalizations: (optional) Defines operations
    that can be used to transform the final output JSON into a normalized form. Operations
    are executed in the order that they appear in the array.
    """

    def __init__(self,
                 pdf=None,
                 word=None,
                 html=None,
                 segment=None,
                 json_normalizations=None):
        """
        Initialize a Conversions object.

        :param PdfSettings pdf: (optional) A list of PDF conversion settings.
        :param WordSettings word: (optional) A list of Word conversion settings.
        :param HtmlSettings html: (optional) A list of HTML conversion settings.
        :param SegmentSettings segment: (optional) A list of Document Segmentation
        settings.
        :param list[NormalizationOperation] json_normalizations: (optional) Defines
        operations that can be used to transform the final output JSON into a normalized
        form. Operations are executed in the order that they appear in the array.
        """
        self.pdf = pdf
        self.word = word
        self.html = html
        self.segment = segment
        self.json_normalizations = json_normalizations

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Conversions object from a json dictionary."""
        args = {}
        if 'pdf' in _dict:
            args['pdf'] = PdfSettings._from_dict(_dict.get('pdf'))
        if 'word' in _dict:
            args['word'] = WordSettings._from_dict(_dict.get('word'))
        if 'html' in _dict:
            args['html'] = HtmlSettings._from_dict(_dict.get('html'))
        if 'segment' in _dict:
            args['segment'] = SegmentSettings._from_dict(_dict.get('segment'))
        if 'json_normalizations' in _dict:
            args['json_normalizations'] = [
                NormalizationOperation._from_dict(x)
                for x in (_dict.get('json_normalizations'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'pdf') and self.pdf is not None:
            _dict['pdf'] = self.pdf._to_dict()
        if hasattr(self, 'word') and self.word is not None:
            _dict['word'] = self.word._to_dict()
        if hasattr(self, 'html') and self.html is not None:
            _dict['html'] = self.html._to_dict()
        if hasattr(self, 'segment') and self.segment is not None:
            _dict['segment'] = self.segment._to_dict()
        if hasattr(
                self,
                'json_normalizations') and self.json_normalizations is not None:
            _dict['json_normalizations'] = [
                x._to_dict() for x in self.json_normalizations
            ]
        return _dict

    def __str__(self):
        """Return a `str` version of this Conversions object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class CreateEventResponse(object):
    """
    An object defining the event being created.

    :attr str type: (optional) The event type that was created.
    :attr EventData data: (optional) Query event data object.
    """

    def __init__(self, type=None, data=None):
        """
        Initialize a CreateEventResponse object.

        :param str type: (optional) The event type that was created.
        :param EventData data: (optional) Query event data object.
        """
        self.type = type
        self.data = data

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a CreateEventResponse object from a json dictionary."""
        args = {}
        if 'type' in _dict:
            args['type'] = _dict.get('type')
        if 'data' in _dict:
            args['data'] = EventData._from_dict(_dict.get('data'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'type') and self.type is not None:
            _dict['type'] = self.type
        if hasattr(self, 'data') and self.data is not None:
            _dict['data'] = self.data._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this CreateEventResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class CredentialDetails(object):
    """
    Object containing details of the stored credentials.
    Obtain credentials for your source from the administrator of the source.

    :attr str credential_type: (optional) The authentication method for this credentials
    definition. The  **credential_type** specified must be supported by the
    **source_type**. The following combinations are possible:
    -  `"source_type": "box"` - valid `credential_type`s: `oauth2`
    -  `"source_type": "salesforce"` - valid `credential_type`s: `username_password`
    -  `"source_type": "sharepoint"` - valid `credential_type`s: `saml` with
    **source_version** of `online`, or `ntml_v1` with **source_version** of `2016`
    -  `"source_type": "web_crawl"` - valid `credential_type`s: `noauth` or `basic`
    -  "source_type": "cloud_object_storage"` - valid `credential_type`s: `aws4_hmac`.
    :attr str client_id: (optional) The **client_id** of the source that these credentials
    connect to. Only valid, and required, with a **credential_type** of `oauth2`.
    :attr str enterprise_id: (optional) The **enterprise_id** of the Box site that these
    credentials connect to. Only valid, and required, with a **source_type** of `box`.
    :attr str url: (optional) The **url** of the source that these credentials connect to.
    Only valid, and required, with a **credential_type** of `username_password`, `noauth`,
    and `basic`.
    :attr str username: (optional) The **username** of the source that these credentials
    connect to. Only valid, and required, with a **credential_type** of `saml`,
    `username_password`, `basic`, or `ntml_v1`.
    :attr str organization_url: (optional) The **organization_url** of the source that
    these credentials connect to. Only valid, and required, with a **credential_type** of
    `saml`.
    :attr str site_collection_path: (optional) The **site_collection.path** of the source
    that these credentials connect to. Only valid, and required, with a **source_type** of
    `sharepoint`.
    :attr str client_secret: (optional) The **client_secret** of the source that these
    credentials connect to. Only valid, and required, with a **credential_type** of
    `oauth2`. This value is never returned and is only used when creating or modifying
    **credentials**.
    :attr str public_key_id: (optional) The **public_key_id** of the source that these
    credentials connect to. Only valid, and required, with a **credential_type** of
    `oauth2`. This value is never returned and is only used when creating or modifying
    **credentials**.
    :attr str private_key: (optional) The **private_key** of the source that these
    credentials connect to. Only valid, and required, with a **credential_type** of
    `oauth2`. This value is never returned and is only used when creating or modifying
    **credentials**.
    :attr str passphrase: (optional) The **passphrase** of the source that these
    credentials connect to. Only valid, and required, with a **credential_type** of
    `oauth2`. This value is never returned and is only used when creating or modifying
    **credentials**.
    :attr str password: (optional) The **password** of the source that these credentials
    connect to. Only valid, and required, with **credential_type**s of `saml`,
    `username_password`, `basic`, or `ntml_v1`.
    **Note:** When used with a **source_type** of `salesforce`, the password consists of
    the Salesforce password and a valid Salesforce security token concatenated. This value
    is never returned and is only used when creating or modifying **credentials**.
    :attr str gateway_id: (optional) The ID of the **gateway** to be connected through
    (when connecting to intranet sites). Only valid with a **credential_type** of
    `noauth`, `basic`, or `ntml_v1`. Gateways are created using the
    `/v1/environments/{environment_id}/gateways` methods.
    :attr str source_version: (optional) The type of Sharepoint repository to connect to.
    Only valid, and required, with a **source_type** of `sharepoint`.
    :attr str web_application_url: (optional) SharePoint OnPrem WebApplication URL. Only
    valid, and required, with a **source_version** of `2016`.
    :attr str domain: (optional) The domain used to log in to your OnPrem SharePoint
    account. Only valid, and required, with a **source_version** of `2016`.
    :attr str endpoint: (optional) The endpoint associated with the cloud object store
    that your are connecting to. Only valid, and required, with a **credential_type** of
    `aws4_hmac`.
    :attr str access_key_id: (optional) The access key ID associated with the cloud object
    store. Only valid, and required, with a **credential_type** of `aws4_hmac`. For more
    infomation, see the [cloud object store
    documentation](https://cloud.ibm.com/docs/services/cloud-object-storage?topic=cloud-object-storage-using-hmac-credentials#using-hmac-credentials).
    :attr str secret_access_key: (optional) The secret access key associated with the
    cloud object store. Only valid, and required, with a **credential_type** of
    `aws4_hmac`. This value is never returned and is only used when creating or modifying
    **credentials**. For more infomation, see the [cloud object store
    documentation](https://cloud.ibm.com/docs/services/cloud-object-storage?topic=cloud-object-storage-using-hmac-credentials#using-hmac-credentials).
    """

    def __init__(self,
                 credential_type=None,
                 client_id=None,
                 enterprise_id=None,
                 url=None,
                 username=None,
                 organization_url=None,
                 site_collection_path=None,
                 client_secret=None,
                 public_key_id=None,
                 private_key=None,
                 passphrase=None,
                 password=None,
                 gateway_id=None,
                 source_version=None,
                 web_application_url=None,
                 domain=None,
                 endpoint=None,
                 access_key_id=None,
                 secret_access_key=None):
        """
        Initialize a CredentialDetails object.

        :param str credential_type: (optional) The authentication method for this
        credentials definition. The  **credential_type** specified must be supported by
        the **source_type**. The following combinations are possible:
        -  `"source_type": "box"` - valid `credential_type`s: `oauth2`
        -  `"source_type": "salesforce"` - valid `credential_type`s: `username_password`
        -  `"source_type": "sharepoint"` - valid `credential_type`s: `saml` with
        **source_version** of `online`, or `ntml_v1` with **source_version** of `2016`
        -  `"source_type": "web_crawl"` - valid `credential_type`s: `noauth` or `basic`
        -  "source_type": "cloud_object_storage"` - valid `credential_type`s: `aws4_hmac`.
        :param str client_id: (optional) The **client_id** of the source that these
        credentials connect to. Only valid, and required, with a **credential_type** of
        `oauth2`.
        :param str enterprise_id: (optional) The **enterprise_id** of the Box site that
        these credentials connect to. Only valid, and required, with a **source_type** of
        `box`.
        :param str url: (optional) The **url** of the source that these credentials
        connect to. Only valid, and required, with a **credential_type** of
        `username_password`, `noauth`, and `basic`.
        :param str username: (optional) The **username** of the source that these
        credentials connect to. Only valid, and required, with a **credential_type** of
        `saml`, `username_password`, `basic`, or `ntml_v1`.
        :param str organization_url: (optional) The **organization_url** of the source
        that these credentials connect to. Only valid, and required, with a
        **credential_type** of `saml`.
        :param str site_collection_path: (optional) The **site_collection.path** of the
        source that these credentials connect to. Only valid, and required, with a
        **source_type** of `sharepoint`.
        :param str client_secret: (optional) The **client_secret** of the source that
        these credentials connect to. Only valid, and required, with a **credential_type**
        of `oauth2`. This value is never returned and is only used when creating or
        modifying **credentials**.
        :param str public_key_id: (optional) The **public_key_id** of the source that
        these credentials connect to. Only valid, and required, with a **credential_type**
        of `oauth2`. This value is never returned and is only used when creating or
        modifying **credentials**.
        :param str private_key: (optional) The **private_key** of the source that these
        credentials connect to. Only valid, and required, with a **credential_type** of
        `oauth2`. This value is never returned and is only used when creating or modifying
        **credentials**.
        :param str passphrase: (optional) The **passphrase** of the source that these
        credentials connect to. Only valid, and required, with a **credential_type** of
        `oauth2`. This value is never returned and is only used when creating or modifying
        **credentials**.
        :param str password: (optional) The **password** of the source that these
        credentials connect to. Only valid, and required, with **credential_type**s of
        `saml`, `username_password`, `basic`, or `ntml_v1`.
        **Note:** When used with a **source_type** of `salesforce`, the password consists
        of the Salesforce password and a valid Salesforce security token concatenated.
        This value is never returned and is only used when creating or modifying
        **credentials**.
        :param str gateway_id: (optional) The ID of the **gateway** to be connected
        through (when connecting to intranet sites). Only valid with a **credential_type**
        of `noauth`, `basic`, or `ntml_v1`. Gateways are created using the
        `/v1/environments/{environment_id}/gateways` methods.
        :param str source_version: (optional) The type of Sharepoint repository to connect
        to. Only valid, and required, with a **source_type** of `sharepoint`.
        :param str web_application_url: (optional) SharePoint OnPrem WebApplication URL.
        Only valid, and required, with a **source_version** of `2016`.
        :param str domain: (optional) The domain used to log in to your OnPrem SharePoint
        account. Only valid, and required, with a **source_version** of `2016`.
        :param str endpoint: (optional) The endpoint associated with the cloud object
        store that your are connecting to. Only valid, and required, with a
        **credential_type** of `aws4_hmac`.
        :param str access_key_id: (optional) The access key ID associated with the cloud
        object store. Only valid, and required, with a **credential_type** of `aws4_hmac`.
        For more infomation, see the [cloud object store
        documentation](https://cloud.ibm.com/docs/services/cloud-object-storage?topic=cloud-object-storage-using-hmac-credentials#using-hmac-credentials).
        :param str secret_access_key: (optional) The secret access key associated with the
        cloud object store. Only valid, and required, with a **credential_type** of
        `aws4_hmac`. This value is never returned and is only used when creating or
        modifying **credentials**. For more infomation, see the [cloud object store
        documentation](https://cloud.ibm.com/docs/services/cloud-object-storage?topic=cloud-object-storage-using-hmac-credentials#using-hmac-credentials).
        """
        self.credential_type = credential_type
        self.client_id = client_id
        self.enterprise_id = enterprise_id
        self.url = url
        self.username = username
        self.organization_url = organization_url
        self.site_collection_path = site_collection_path
        self.client_secret = client_secret
        self.public_key_id = public_key_id
        self.private_key = private_key
        self.passphrase = passphrase
        self.password = password
        self.gateway_id = gateway_id
        self.source_version = source_version
        self.web_application_url = web_application_url
        self.domain = domain
        self.endpoint = endpoint
        self.access_key_id = access_key_id
        self.secret_access_key = secret_access_key

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a CredentialDetails object from a json dictionary."""
        args = {}
        if 'credential_type' in _dict:
            args['credential_type'] = _dict.get('credential_type')
        if 'client_id' in _dict:
            args['client_id'] = _dict.get('client_id')
        if 'enterprise_id' in _dict:
            args['enterprise_id'] = _dict.get('enterprise_id')
        if 'url' in _dict:
            args['url'] = _dict.get('url')
        if 'username' in _dict:
            args['username'] = _dict.get('username')
        if 'organization_url' in _dict:
            args['organization_url'] = _dict.get('organization_url')
        if 'site_collection.path' in _dict:
            args['site_collection_path'] = _dict.get('site_collection.path')
        if 'client_secret' in _dict:
            args['client_secret'] = _dict.get('client_secret')
        if 'public_key_id' in _dict:
            args['public_key_id'] = _dict.get('public_key_id')
        if 'private_key' in _dict:
            args['private_key'] = _dict.get('private_key')
        if 'passphrase' in _dict:
            args['passphrase'] = _dict.get('passphrase')
        if 'password' in _dict:
            args['password'] = _dict.get('password')
        if 'gateway_id' in _dict:
            args['gateway_id'] = _dict.get('gateway_id')
        if 'source_version' in _dict:
            args['source_version'] = _dict.get('source_version')
        if 'web_application_url' in _dict:
            args['web_application_url'] = _dict.get('web_application_url')
        if 'domain' in _dict:
            args['domain'] = _dict.get('domain')
        if 'endpoint' in _dict:
            args['endpoint'] = _dict.get('endpoint')
        if 'access_key_id' in _dict:
            args['access_key_id'] = _dict.get('access_key_id')
        if 'secret_access_key' in _dict:
            args['secret_access_key'] = _dict.get('secret_access_key')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self,
                   'credential_type') and self.credential_type is not None:
            _dict['credential_type'] = self.credential_type
        if hasattr(self, 'client_id') and self.client_id is not None:
            _dict['client_id'] = self.client_id
        if hasattr(self, 'enterprise_id') and self.enterprise_id is not None:
            _dict['enterprise_id'] = self.enterprise_id
        if hasattr(self, 'url') and self.url is not None:
            _dict['url'] = self.url
        if hasattr(self, 'username') and self.username is not None:
            _dict['username'] = self.username
        if hasattr(self,
                   'organization_url') and self.organization_url is not None:
            _dict['organization_url'] = self.organization_url
        if hasattr(self, 'site_collection_path'
                  ) and self.site_collection_path is not None:
            _dict['site_collection.path'] = self.site_collection_path
        if hasattr(self, 'client_secret') and self.client_secret is not None:
            _dict['client_secret'] = self.client_secret
        if hasattr(self, 'public_key_id') and self.public_key_id is not None:
            _dict['public_key_id'] = self.public_key_id
        if hasattr(self, 'private_key') and self.private_key is not None:
            _dict['private_key'] = self.private_key
        if hasattr(self, 'passphrase') and self.passphrase is not None:
            _dict['passphrase'] = self.passphrase
        if hasattr(self, 'password') and self.password is not None:
            _dict['password'] = self.password
        if hasattr(self, 'gateway_id') and self.gateway_id is not None:
            _dict['gateway_id'] = self.gateway_id
        if hasattr(self, 'source_version') and self.source_version is not None:
            _dict['source_version'] = self.source_version
        if hasattr(
                self,
                'web_application_url') and self.web_application_url is not None:
            _dict['web_application_url'] = self.web_application_url
        if hasattr(self, 'domain') and self.domain is not None:
            _dict['domain'] = self.domain
        if hasattr(self, 'endpoint') and self.endpoint is not None:
            _dict['endpoint'] = self.endpoint
        if hasattr(self, 'access_key_id') and self.access_key_id is not None:
            _dict['access_key_id'] = self.access_key_id
        if hasattr(self,
                   'secret_access_key') and self.secret_access_key is not None:
            _dict['secret_access_key'] = self.secret_access_key
        return _dict

    def __str__(self):
        """Return a `str` version of this CredentialDetails object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Credentials(object):
    """
    Object containing credential information.

    :attr str credential_id: (optional) Unique identifier for this set of credentials.
    :attr str source_type: (optional) The source that this credentials object connects to.
    -  `box` indicates the credentials are used to connect an instance of Enterprise Box.
    -  `salesforce` indicates the credentials are used to connect to Salesforce.
    -  `sharepoint` indicates the credentials are used to connect to Microsoft SharePoint
    Online.
    -  `web_crawl` indicates the credentials are used to perform a web crawl.
    =  `cloud_object_storage` indicates the credentials are used to connect to an IBM
    Cloud Object Store.
    :attr CredentialDetails credential_details: (optional) Object containing details of
    the stored credentials.
    Obtain credentials for your source from the administrator of the source.
    """

    def __init__(self,
                 credential_id=None,
                 source_type=None,
                 credential_details=None):
        """
        Initialize a Credentials object.

        :param str credential_id: (optional) Unique identifier for this set of
        credentials.
        :param str source_type: (optional) The source that this credentials object
        connects to.
        -  `box` indicates the credentials are used to connect an instance of Enterprise
        Box.
        -  `salesforce` indicates the credentials are used to connect to Salesforce.
        -  `sharepoint` indicates the credentials are used to connect to Microsoft
        SharePoint Online.
        -  `web_crawl` indicates the credentials are used to perform a web crawl.
        =  `cloud_object_storage` indicates the credentials are used to connect to an IBM
        Cloud Object Store.
        :param CredentialDetails credential_details: (optional) Object containing details
        of the stored credentials.
        Obtain credentials for your source from the administrator of the source.
        """
        self.credential_id = credential_id
        self.source_type = source_type
        self.credential_details = credential_details

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Credentials object from a json dictionary."""
        args = {}
        if 'credential_id' in _dict:
            args['credential_id'] = _dict.get('credential_id')
        if 'source_type' in _dict:
            args['source_type'] = _dict.get('source_type')
        if 'credential_details' in _dict:
            args['credential_details'] = CredentialDetails._from_dict(
                _dict.get('credential_details'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'credential_id') and self.credential_id is not None:
            _dict['credential_id'] = self.credential_id
        if hasattr(self, 'source_type') and self.source_type is not None:
            _dict['source_type'] = self.source_type
        if hasattr(
                self,
                'credential_details') and self.credential_details is not None:
            _dict['credential_details'] = self.credential_details._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this Credentials object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class CredentialsList(object):
    """
    CredentialsList.

    :attr list[Credentials] credentials: (optional) An array of credential definitions
    that were created for this instance.
    """

    def __init__(self, credentials=None):
        """
        Initialize a CredentialsList object.

        :param list[Credentials] credentials: (optional) An array of credential
        definitions that were created for this instance.
        """
        self.credentials = credentials

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a CredentialsList object from a json dictionary."""
        args = {}
        if 'credentials' in _dict:
            args['credentials'] = [
                Credentials._from_dict(x) for x in (_dict.get('credentials'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'credentials') and self.credentials is not None:
            _dict['credentials'] = [x._to_dict() for x in self.credentials]
        return _dict

    def __str__(self):
        """Return a `str` version of this CredentialsList object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DeleteCollectionResponse(object):
    """
    DeleteCollectionResponse.

    :attr str collection_id: The unique identifier of the collection that is being
    deleted.
    :attr str status: The status of the collection. The status of a successful deletion
    operation is `deleted`.
    """

    def __init__(self, collection_id, status):
        """
        Initialize a DeleteCollectionResponse object.

        :param str collection_id: The unique identifier of the collection that is being
        deleted.
        :param str status: The status of the collection. The status of a successful
        deletion operation is `deleted`.
        """
        self.collection_id = collection_id
        self.status = status

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DeleteCollectionResponse object from a json dictionary."""
        args = {}
        if 'collection_id' in _dict:
            args['collection_id'] = _dict.get('collection_id')
        else:
            raise ValueError(
                'Required property \'collection_id\' not present in DeleteCollectionResponse JSON'
            )
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        else:
            raise ValueError(
                'Required property \'status\' not present in DeleteCollectionResponse JSON'
            )
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'collection_id') and self.collection_id is not None:
            _dict['collection_id'] = self.collection_id
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        return _dict

    def __str__(self):
        """Return a `str` version of this DeleteCollectionResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DeleteConfigurationResponse(object):
    """
    DeleteConfigurationResponse.

    :attr str configuration_id: The unique identifier for the configuration.
    :attr str status: Status of the configuration. A deleted configuration has the status
    deleted.
    :attr list[Notice] notices: (optional) An array of notice messages, if any.
    """

    def __init__(self, configuration_id, status, notices=None):
        """
        Initialize a DeleteConfigurationResponse object.

        :param str configuration_id: The unique identifier for the configuration.
        :param str status: Status of the configuration. A deleted configuration has the
        status deleted.
        :param list[Notice] notices: (optional) An array of notice messages, if any.
        """
        self.configuration_id = configuration_id
        self.status = status
        self.notices = notices

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DeleteConfigurationResponse object from a json dictionary."""
        args = {}
        if 'configuration_id' in _dict:
            args['configuration_id'] = _dict.get('configuration_id')
        else:
            raise ValueError(
                'Required property \'configuration_id\' not present in DeleteConfigurationResponse JSON'
            )
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        else:
            raise ValueError(
                'Required property \'status\' not present in DeleteConfigurationResponse JSON'
            )
        if 'notices' in _dict:
            args['notices'] = [
                Notice._from_dict(x) for x in (_dict.get('notices'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self,
                   'configuration_id') and self.configuration_id is not None:
            _dict['configuration_id'] = self.configuration_id
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        if hasattr(self, 'notices') and self.notices is not None:
            _dict['notices'] = [x._to_dict() for x in self.notices]
        return _dict

    def __str__(self):
        """Return a `str` version of this DeleteConfigurationResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DeleteCredentials(object):
    """
    Object returned after credentials are deleted.

    :attr str credential_id: (optional) The unique identifier of the credentials that have
    been deleted.
    :attr str status: (optional) The status of the deletion request.
    """

    def __init__(self, credential_id=None, status=None):
        """
        Initialize a DeleteCredentials object.

        :param str credential_id: (optional) The unique identifier of the credentials that
        have been deleted.
        :param str status: (optional) The status of the deletion request.
        """
        self.credential_id = credential_id
        self.status = status

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DeleteCredentials object from a json dictionary."""
        args = {}
        if 'credential_id' in _dict:
            args['credential_id'] = _dict.get('credential_id')
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'credential_id') and self.credential_id is not None:
            _dict['credential_id'] = self.credential_id
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        return _dict

    def __str__(self):
        """Return a `str` version of this DeleteCredentials object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DeleteDocumentResponse(object):
    """
    DeleteDocumentResponse.

    :attr str document_id: (optional) The unique identifier of the document.
    :attr str status: (optional) Status of the document. A deleted document has the status
    deleted.
    """

    def __init__(self, document_id=None, status=None):
        """
        Initialize a DeleteDocumentResponse object.

        :param str document_id: (optional) The unique identifier of the document.
        :param str status: (optional) Status of the document. A deleted document has the
        status deleted.
        """
        self.document_id = document_id
        self.status = status

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DeleteDocumentResponse object from a json dictionary."""
        args = {}
        if 'document_id' in _dict:
            args['document_id'] = _dict.get('document_id')
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'document_id') and self.document_id is not None:
            _dict['document_id'] = self.document_id
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        return _dict

    def __str__(self):
        """Return a `str` version of this DeleteDocumentResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DeleteEnvironmentResponse(object):
    """
    DeleteEnvironmentResponse.

    :attr str environment_id: The unique identifier for the environment.
    :attr str status: Status of the environment.
    """

    def __init__(self, environment_id, status):
        """
        Initialize a DeleteEnvironmentResponse object.

        :param str environment_id: The unique identifier for the environment.
        :param str status: Status of the environment.
        """
        self.environment_id = environment_id
        self.status = status

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DeleteEnvironmentResponse object from a json dictionary."""
        args = {}
        if 'environment_id' in _dict:
            args['environment_id'] = _dict.get('environment_id')
        else:
            raise ValueError(
                'Required property \'environment_id\' not present in DeleteEnvironmentResponse JSON'
            )
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        else:
            raise ValueError(
                'Required property \'status\' not present in DeleteEnvironmentResponse JSON'
            )
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'environment_id') and self.environment_id is not None:
            _dict['environment_id'] = self.environment_id
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        return _dict

    def __str__(self):
        """Return a `str` version of this DeleteEnvironmentResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DiskUsage(object):
    """
    Summary of the disk usage statistics for the environment.

    :attr int used_bytes: (optional) Number of bytes within the environment's disk
    capacity that are currently used to store data.
    :attr int maximum_allowed_bytes: (optional) Total number of bytes available in the
    environment's disk capacity.
    """

    def __init__(self, used_bytes=None, maximum_allowed_bytes=None):
        """
        Initialize a DiskUsage object.

        :param int used_bytes: (optional) Number of bytes within the environment's disk
        capacity that are currently used to store data.
        :param int maximum_allowed_bytes: (optional) Total number of bytes available in
        the environment's disk capacity.
        """
        self.used_bytes = used_bytes
        self.maximum_allowed_bytes = maximum_allowed_bytes

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DiskUsage object from a json dictionary."""
        args = {}
        if 'used_bytes' in _dict:
            args['used_bytes'] = _dict.get('used_bytes')
        if 'maximum_allowed_bytes' in _dict:
            args['maximum_allowed_bytes'] = _dict.get('maximum_allowed_bytes')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'used_bytes') and self.used_bytes is not None:
            _dict['used_bytes'] = self.used_bytes
        if hasattr(self, 'maximum_allowed_bytes'
                  ) and self.maximum_allowed_bytes is not None:
            _dict['maximum_allowed_bytes'] = self.maximum_allowed_bytes
        return _dict

    def __str__(self):
        """Return a `str` version of this DiskUsage object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DocumentAccepted(object):
    """
    DocumentAccepted.

    :attr str document_id: (optional) The unique identifier of the ingested document.
    :attr str status: (optional) Status of the document in the ingestion process. A status
    of `processing` is returned for documents that are ingested with a *version* date
    before `2019-01-01`. The `pending` status is returned for all others.
    :attr list[Notice] notices: (optional) Array of notices produced by the
    document-ingestion process.
    """

    def __init__(self, document_id=None, status=None, notices=None):
        """
        Initialize a DocumentAccepted object.

        :param str document_id: (optional) The unique identifier of the ingested document.
        :param str status: (optional) Status of the document in the ingestion process. A
        status of `processing` is returned for documents that are ingested with a
        *version* date before `2019-01-01`. The `pending` status is returned for all
        others.
        :param list[Notice] notices: (optional) Array of notices produced by the
        document-ingestion process.
        """
        self.document_id = document_id
        self.status = status
        self.notices = notices

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DocumentAccepted object from a json dictionary."""
        args = {}
        if 'document_id' in _dict:
            args['document_id'] = _dict.get('document_id')
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        if 'notices' in _dict:
            args['notices'] = [
                Notice._from_dict(x) for x in (_dict.get('notices'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'document_id') and self.document_id is not None:
            _dict['document_id'] = self.document_id
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        if hasattr(self, 'notices') and self.notices is not None:
            _dict['notices'] = [x._to_dict() for x in self.notices]
        return _dict

    def __str__(self):
        """Return a `str` version of this DocumentAccepted object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DocumentCounts(object):
    """
    DocumentCounts.

    :attr int available: (optional) The total number of available documents in the
    collection.
    :attr int processing: (optional) The number of documents in the collection that are
    currently being processed.
    :attr int failed: (optional) The number of documents in the collection that failed to
    be ingested.
    :attr int pending: (optional) The number of documents that have been uploaded to the
    collection, but have not yet started processing.
    """

    def __init__(self,
                 available=None,
                 processing=None,
                 failed=None,
                 pending=None):
        """
        Initialize a DocumentCounts object.

        :param int available: (optional) The total number of available documents in the
        collection.
        :param int processing: (optional) The number of documents in the collection that
        are currently being processed.
        :param int failed: (optional) The number of documents in the collection that
        failed to be ingested.
        :param int pending: (optional) The number of documents that have been uploaded to
        the collection, but have not yet started processing.
        """
        self.available = available
        self.processing = processing
        self.failed = failed
        self.pending = pending

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DocumentCounts object from a json dictionary."""
        args = {}
        if 'available' in _dict:
            args['available'] = _dict.get('available')
        if 'processing' in _dict:
            args['processing'] = _dict.get('processing')
        if 'failed' in _dict:
            args['failed'] = _dict.get('failed')
        if 'pending' in _dict:
            args['pending'] = _dict.get('pending')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'available') and self.available is not None:
            _dict['available'] = self.available
        if hasattr(self, 'processing') and self.processing is not None:
            _dict['processing'] = self.processing
        if hasattr(self, 'failed') and self.failed is not None:
            _dict['failed'] = self.failed
        if hasattr(self, 'pending') and self.pending is not None:
            _dict['pending'] = self.pending
        return _dict

    def __str__(self):
        """Return a `str` version of this DocumentCounts object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DocumentSnapshot(object):
    """
    DocumentSnapshot.

    :attr str step: (optional) The step in the document conversion process that the
    snapshot object represents.
    :attr dict snapshot: (optional) Snapshot of the conversion.
    """

    def __init__(self, step=None, snapshot=None):
        """
        Initialize a DocumentSnapshot object.

        :param str step: (optional) The step in the document conversion process that the
        snapshot object represents.
        :param dict snapshot: (optional) Snapshot of the conversion.
        """
        self.step = step
        self.snapshot = snapshot

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DocumentSnapshot object from a json dictionary."""
        args = {}
        if 'step' in _dict:
            args['step'] = _dict.get('step')
        if 'snapshot' in _dict:
            args['snapshot'] = _dict.get('snapshot')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'step') and self.step is not None:
            _dict['step'] = self.step
        if hasattr(self, 'snapshot') and self.snapshot is not None:
            _dict['snapshot'] = self.snapshot
        return _dict

    def __str__(self):
        """Return a `str` version of this DocumentSnapshot object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DocumentStatus(object):
    """
    Status information about a submitted document.

    :attr str document_id: The unique identifier of the document.
    :attr str configuration_id: (optional) The unique identifier for the configuration.
    :attr str status: Status of the document in the ingestion process.
    :attr str status_description: Description of the document status.
    :attr str filename: (optional) Name of the original source file (if available).
    :attr str file_type: (optional) The type of the original source file.
    :attr str sha1: (optional) The SHA-1 hash of the original source file (formatted as a
    hexadecimal string).
    :attr list[Notice] notices: Array of notices produced by the document-ingestion
    process.
    """

    def __init__(self,
                 document_id,
                 status,
                 status_description,
                 notices,
                 configuration_id=None,
                 filename=None,
                 file_type=None,
                 sha1=None):
        """
        Initialize a DocumentStatus object.

        :param str document_id: The unique identifier of the document.
        :param str status: Status of the document in the ingestion process.
        :param str status_description: Description of the document status.
        :param list[Notice] notices: Array of notices produced by the document-ingestion
        process.
        :param str configuration_id: (optional) The unique identifier for the
        configuration.
        :param str filename: (optional) Name of the original source file (if available).
        :param str file_type: (optional) The type of the original source file.
        :param str sha1: (optional) The SHA-1 hash of the original source file (formatted
        as a hexadecimal string).
        """
        self.document_id = document_id
        self.configuration_id = configuration_id
        self.status = status
        self.status_description = status_description
        self.filename = filename
        self.file_type = file_type
        self.sha1 = sha1
        self.notices = notices

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DocumentStatus object from a json dictionary."""
        args = {}
        if 'document_id' in _dict:
            args['document_id'] = _dict.get('document_id')
        else:
            raise ValueError(
                'Required property \'document_id\' not present in DocumentStatus JSON'
            )
        if 'configuration_id' in _dict:
            args['configuration_id'] = _dict.get('configuration_id')
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        else:
            raise ValueError(
                'Required property \'status\' not present in DocumentStatus JSON'
            )
        if 'status_description' in _dict:
            args['status_description'] = _dict.get('status_description')
        else:
            raise ValueError(
                'Required property \'status_description\' not present in DocumentStatus JSON'
            )
        if 'filename' in _dict:
            args['filename'] = _dict.get('filename')
        if 'file_type' in _dict:
            args['file_type'] = _dict.get('file_type')
        if 'sha1' in _dict:
            args['sha1'] = _dict.get('sha1')
        if 'notices' in _dict:
            args['notices'] = [
                Notice._from_dict(x) for x in (_dict.get('notices'))
            ]
        else:
            raise ValueError(
                'Required property \'notices\' not present in DocumentStatus JSON'
            )
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'document_id') and self.document_id is not None:
            _dict['document_id'] = self.document_id
        if hasattr(self,
                   'configuration_id') and self.configuration_id is not None:
            _dict['configuration_id'] = self.configuration_id
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        if hasattr(
                self,
                'status_description') and self.status_description is not None:
            _dict['status_description'] = self.status_description
        if hasattr(self, 'filename') and self.filename is not None:
            _dict['filename'] = self.filename
        if hasattr(self, 'file_type') and self.file_type is not None:
            _dict['file_type'] = self.file_type
        if hasattr(self, 'sha1') and self.sha1 is not None:
            _dict['sha1'] = self.sha1
        if hasattr(self, 'notices') and self.notices is not None:
            _dict['notices'] = [x._to_dict() for x in self.notices]
        return _dict

    def __str__(self):
        """Return a `str` version of this DocumentStatus object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Enrichment(object):
    """
    Enrichment.

    :attr str description: (optional) Describes what the enrichment step does.
    :attr str destination_field: Field where enrichments will be stored. This field must
    already exist or be at most 1 level deeper than an existing field. For example, if
    `text` is a top-level field with no sub-fields, `text.foo` is a valid destination but
    `text.foo.bar` is not.
    :attr str source_field: Field to be enriched.
    Arrays can be specified as the **source_field** if the **enrichment** service for this
    enrichment is set to `natural_language_undstanding`.
    :attr bool overwrite: (optional) Indicates that the enrichments will overwrite the
    destination_field field if it already exists.
    :attr str enrichment_name: Name of the enrichment service to call. Current options are
    `natural_language_understanding` and `elements`.
     When using `natual_language_understanding`, the **options** object must contain
    Natural Language Understanding options.
     When using `elements` the **options** object must contain Element Classification
    options. Additionally, when using the `elements` enrichment the configuration
    specified and files ingested must meet all the criteria specified in [the
    documentation](https://cloud.ibm.com/docs/services/discovery?topic=discovery-element-classification#element-classification).
    :attr bool ignore_downstream_errors: (optional) If true, then most errors generated
    during the enrichment process will be treated as warnings and will not cause the
    document to fail processing.
    :attr EnrichmentOptions options: (optional) An object representing the configuration
    options to use for the `elements` enrichment.
    """

    def __init__(self,
                 destination_field,
                 source_field,
                 enrichment_name,
                 description=None,
                 overwrite=None,
                 ignore_downstream_errors=None,
                 options=None):
        """
        Initialize a Enrichment object.

        :param str destination_field: Field where enrichments will be stored. This field
        must already exist or be at most 1 level deeper than an existing field. For
        example, if `text` is a top-level field with no sub-fields, `text.foo` is a valid
        destination but `text.foo.bar` is not.
        :param str source_field: Field to be enriched.
        Arrays can be specified as the **source_field** if the **enrichment** service for
        this enrichment is set to `natural_language_undstanding`.
        :param str enrichment_name: Name of the enrichment service to call. Current
        options are `natural_language_understanding` and `elements`.
         When using `natual_language_understanding`, the **options** object must contain
        Natural Language Understanding options.
         When using `elements` the **options** object must contain Element Classification
        options. Additionally, when using the `elements` enrichment the configuration
        specified and files ingested must meet all the criteria specified in [the
        documentation](https://cloud.ibm.com/docs/services/discovery?topic=discovery-element-classification#element-classification).
        :param str description: (optional) Describes what the enrichment step does.
        :param bool overwrite: (optional) Indicates that the enrichments will overwrite
        the destination_field field if it already exists.
        :param bool ignore_downstream_errors: (optional) If true, then most errors
        generated during the enrichment process will be treated as warnings and will not
        cause the document to fail processing.
        :param EnrichmentOptions options: (optional) An object representing the
        configuration options to use for the `elements` enrichment.
        """
        self.description = description
        self.destination_field = destination_field
        self.source_field = source_field
        self.overwrite = overwrite
        self.enrichment_name = enrichment_name
        self.ignore_downstream_errors = ignore_downstream_errors
        self.options = options

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Enrichment object from a json dictionary."""
        args = {}
        if 'description' in _dict:
            args['description'] = _dict.get('description')
        if 'destination_field' in _dict:
            args['destination_field'] = _dict.get('destination_field')
        else:
            raise ValueError(
                'Required property \'destination_field\' not present in Enrichment JSON'
            )
        if 'source_field' in _dict:
            args['source_field'] = _dict.get('source_field')
        else:
            raise ValueError(
                'Required property \'source_field\' not present in Enrichment JSON'
            )
        if 'overwrite' in _dict:
            args['overwrite'] = _dict.get('overwrite')
        if 'enrichment' in _dict or 'enrichment_name' in _dict:
            args['enrichment_name'] = _dict.get('enrichment') or _dict.get(
                'enrichment_name')
        else:
            raise ValueError(
                'Required property \'enrichment\' not present in Enrichment JSON'
            )
        if 'ignore_downstream_errors' in _dict:
            args['ignore_downstream_errors'] = _dict.get(
                'ignore_downstream_errors')
        if 'options' in _dict:
            args['options'] = EnrichmentOptions._from_dict(_dict.get('options'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'description') and self.description is not None:
            _dict['description'] = self.description
        if hasattr(self,
                   'destination_field') and self.destination_field is not None:
            _dict['destination_field'] = self.destination_field
        if hasattr(self, 'source_field') and self.source_field is not None:
            _dict['source_field'] = self.source_field
        if hasattr(self, 'overwrite') and self.overwrite is not None:
            _dict['overwrite'] = self.overwrite
        if hasattr(self,
                   'enrichment_name') and self.enrichment_name is not None:
            _dict['enrichment'] = self.enrichment_name
        if hasattr(self, 'ignore_downstream_errors'
                  ) and self.ignore_downstream_errors is not None:
            _dict['ignore_downstream_errors'] = self.ignore_downstream_errors
        if hasattr(self, 'options') and self.options is not None:
            _dict['options'] = self.options._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this Enrichment object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class EnrichmentOptions(object):
    """
    An object representing the configuration options to use for the `elements` enrichment.

    :attr NluEnrichmentFeatures features: (optional)
    :attr str language: (optional) ISO 639-1 code indicating the language to use for the
    analysis. This code overrides the automatic language detection performed by the
    service. Valid codes are `ar` (Arabic), `en` (English), `fr` (French), `de` (German),
    `it` (Italian), `pt` (Portuguese), `ru` (Russian), `es` (Spanish), and `sv` (Swedish).
    **Note:** Not all features support all languages, automatic detection is recommended.
    :attr str model: (optional) *For use with `elements` enrichments only.* The element
    extraction model to use. Models available are: `contract`.
    """

    def __init__(self, features=None, language=None, model=None):
        """
        Initialize a EnrichmentOptions object.

        :param NluEnrichmentFeatures features: (optional)
        :param str language: (optional) ISO 639-1 code indicating the language to use for
        the analysis. This code overrides the automatic language detection performed by
        the service. Valid codes are `ar` (Arabic), `en` (English), `fr` (French), `de`
        (German), `it` (Italian), `pt` (Portuguese), `ru` (Russian), `es` (Spanish), and
        `sv` (Swedish). **Note:** Not all features support all languages, automatic
        detection is recommended.
        :param str model: (optional) *For use with `elements` enrichments only.* The
        element extraction model to use. Models available are: `contract`.
        """
        self.features = features
        self.language = language
        self.model = model

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a EnrichmentOptions object from a json dictionary."""
        args = {}
        if 'features' in _dict:
            args['features'] = NluEnrichmentFeatures._from_dict(
                _dict.get('features'))
        if 'language' in _dict:
            args['language'] = _dict.get('language')
        if 'model' in _dict:
            args['model'] = _dict.get('model')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'features') and self.features is not None:
            _dict['features'] = self.features._to_dict()
        if hasattr(self, 'language') and self.language is not None:
            _dict['language'] = self.language
        if hasattr(self, 'model') and self.model is not None:
            _dict['model'] = self.model
        return _dict

    def __str__(self):
        """Return a `str` version of this EnrichmentOptions object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Environment(object):
    """
    Details about an environment.

    :attr str environment_id: (optional) Unique identifier for the environment.
    :attr str name: (optional) Name that identifies the environment.
    :attr str description: (optional) Description of the environment.
    :attr datetime created: (optional) Creation date of the environment, in the format
    `yyyy-MM-dd'T'HH:mm:ss.SSS'Z'`.
    :attr datetime updated: (optional) Date of most recent environment update, in the
    format `yyyy-MM-dd'T'HH:mm:ss.SSS'Z'`.
    :attr str status: (optional) Current status of the environment. `resizing` is
    displayed when a request to increase the environment size has been made, but is still
    in the process of being completed.
    :attr bool read_only: (optional) If `true`, the environment contains read-only
    collections that are maintained by IBM.
    :attr str size: (optional) Current size of the environment.
    :attr str requested_size: (optional) The new size requested for this environment. Only
    returned when the environment *status* is `resizing`.
    *Note:* Querying and indexing can still be performed during an environment upsize.
    :attr IndexCapacity index_capacity: (optional) Details about the resource usage and
    capacity of the environment.
    :attr SearchStatus search_status: (optional) Information about the Continuous
    Relevancy Training for this environment.
    """

    def __init__(self,
                 environment_id=None,
                 name=None,
                 description=None,
                 created=None,
                 updated=None,
                 status=None,
                 read_only=None,
                 size=None,
                 requested_size=None,
                 index_capacity=None,
                 search_status=None):
        """
        Initialize a Environment object.

        :param str environment_id: (optional) Unique identifier for the environment.
        :param str name: (optional) Name that identifies the environment.
        :param str description: (optional) Description of the environment.
        :param datetime created: (optional) Creation date of the environment, in the
        format `yyyy-MM-dd'T'HH:mm:ss.SSS'Z'`.
        :param datetime updated: (optional) Date of most recent environment update, in the
        format `yyyy-MM-dd'T'HH:mm:ss.SSS'Z'`.
        :param str status: (optional) Current status of the environment. `resizing` is
        displayed when a request to increase the environment size has been made, but is
        still in the process of being completed.
        :param bool read_only: (optional) If `true`, the environment contains read-only
        collections that are maintained by IBM.
        :param str size: (optional) Current size of the environment.
        :param str requested_size: (optional) The new size requested for this environment.
        Only returned when the environment *status* is `resizing`.
        *Note:* Querying and indexing can still be performed during an environment upsize.
        :param IndexCapacity index_capacity: (optional) Details about the resource usage
        and capacity of the environment.
        :param SearchStatus search_status: (optional) Information about the Continuous
        Relevancy Training for this environment.
        """
        self.environment_id = environment_id
        self.name = name
        self.description = description
        self.created = created
        self.updated = updated
        self.status = status
        self.read_only = read_only
        self.size = size
        self.requested_size = requested_size
        self.index_capacity = index_capacity
        self.search_status = search_status

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Environment object from a json dictionary."""
        args = {}
        if 'environment_id' in _dict:
            args['environment_id'] = _dict.get('environment_id')
        if 'name' in _dict:
            args['name'] = _dict.get('name')
        if 'description' in _dict:
            args['description'] = _dict.get('description')
        if 'created' in _dict:
            args['created'] = string_to_datetime(_dict.get('created'))
        if 'updated' in _dict:
            args['updated'] = string_to_datetime(_dict.get('updated'))
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        if 'read_only' in _dict:
            args['read_only'] = _dict.get('read_only')
        if 'size' in _dict:
            args['size'] = _dict.get('size')
        if 'requested_size' in _dict:
            args['requested_size'] = _dict.get('requested_size')
        if 'index_capacity' in _dict:
            args['index_capacity'] = IndexCapacity._from_dict(
                _dict.get('index_capacity'))
        if 'search_status' in _dict:
            args['search_status'] = SearchStatus._from_dict(
                _dict.get('search_status'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'environment_id') and self.environment_id is not None:
            _dict['environment_id'] = self.environment_id
        if hasattr(self, 'name') and self.name is not None:
            _dict['name'] = self.name
        if hasattr(self, 'description') and self.description is not None:
            _dict['description'] = self.description
        if hasattr(self, 'created') and self.created is not None:
            _dict['created'] = datetime_to_string(self.created)
        if hasattr(self, 'updated') and self.updated is not None:
            _dict['updated'] = datetime_to_string(self.updated)
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        if hasattr(self, 'read_only') and self.read_only is not None:
            _dict['read_only'] = self.read_only
        if hasattr(self, 'size') and self.size is not None:
            _dict['size'] = self.size
        if hasattr(self, 'requested_size') and self.requested_size is not None:
            _dict['requested_size'] = self.requested_size
        if hasattr(self, 'index_capacity') and self.index_capacity is not None:
            _dict['index_capacity'] = self.index_capacity._to_dict()
        if hasattr(self, 'search_status') and self.search_status is not None:
            _dict['search_status'] = self.search_status._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this Environment object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class EnvironmentDocuments(object):
    """
    Summary of the document usage statistics for the environment.

    :attr int indexed: (optional) Number of documents indexed for the environment.
    :attr int maximum_allowed: (optional) Total number of documents allowed in the
    environment's capacity.
    """

    def __init__(self, indexed=None, maximum_allowed=None):
        """
        Initialize a EnvironmentDocuments object.

        :param int indexed: (optional) Number of documents indexed for the environment.
        :param int maximum_allowed: (optional) Total number of documents allowed in the
        environment's capacity.
        """
        self.indexed = indexed
        self.maximum_allowed = maximum_allowed

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a EnvironmentDocuments object from a json dictionary."""
        args = {}
        if 'indexed' in _dict:
            args['indexed'] = _dict.get('indexed')
        if 'maximum_allowed' in _dict:
            args['maximum_allowed'] = _dict.get('maximum_allowed')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'indexed') and self.indexed is not None:
            _dict['indexed'] = self.indexed
        if hasattr(self,
                   'maximum_allowed') and self.maximum_allowed is not None:
            _dict['maximum_allowed'] = self.maximum_allowed
        return _dict

    def __str__(self):
        """Return a `str` version of this EnvironmentDocuments object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class EventData(object):
    """
    Query event data object.

    :attr str environment_id: The **environment_id** associated with the query that the
    event is associated with.
    :attr str session_token: The session token that was returned as part of the query
    results that this event is associated with.
    :attr datetime client_timestamp: (optional) The optional timestamp for the event that
    was created. If not provided, the time that the event was created in the log was used.
    :attr int display_rank: (optional) The rank of the result item which the event is
    associated with.
    :attr str collection_id: The **collection_id** of the document that this event is
    associated with.
    :attr str document_id: The **document_id** of the document that this event is
    associated with.
    :attr str query_id: (optional) The query identifier stored in the log. The query and
    any events associated with that query are stored with the same **query_id**.
    """

    def __init__(self,
                 environment_id,
                 session_token,
                 collection_id,
                 document_id,
                 client_timestamp=None,
                 display_rank=None,
                 query_id=None):
        """
        Initialize a EventData object.

        :param str environment_id: The **environment_id** associated with the query that
        the event is associated with.
        :param str session_token: The session token that was returned as part of the query
        results that this event is associated with.
        :param str collection_id: The **collection_id** of the document that this event is
        associated with.
        :param str document_id: The **document_id** of the document that this event is
        associated with.
        :param datetime client_timestamp: (optional) The optional timestamp for the event
        that was created. If not provided, the time that the event was created in the log
        was used.
        :param int display_rank: (optional) The rank of the result item which the event is
        associated with.
        :param str query_id: (optional) The query identifier stored in the log. The query
        and any events associated with that query are stored with the same **query_id**.
        """
        self.environment_id = environment_id
        self.session_token = session_token
        self.client_timestamp = client_timestamp
        self.display_rank = display_rank
        self.collection_id = collection_id
        self.document_id = document_id
        self.query_id = query_id

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a EventData object from a json dictionary."""
        args = {}
        if 'environment_id' in _dict:
            args['environment_id'] = _dict.get('environment_id')
        else:
            raise ValueError(
                'Required property \'environment_id\' not present in EventData JSON'
            )
        if 'session_token' in _dict:
            args['session_token'] = _dict.get('session_token')
        else:
            raise ValueError(
                'Required property \'session_token\' not present in EventData JSON'
            )
        if 'client_timestamp' in _dict:
            args['client_timestamp'] = string_to_datetime(
                _dict.get('client_timestamp'))
        if 'display_rank' in _dict:
            args['display_rank'] = _dict.get('display_rank')
        if 'collection_id' in _dict:
            args['collection_id'] = _dict.get('collection_id')
        else:
            raise ValueError(
                'Required property \'collection_id\' not present in EventData JSON'
            )
        if 'document_id' in _dict:
            args['document_id'] = _dict.get('document_id')
        else:
            raise ValueError(
                'Required property \'document_id\' not present in EventData JSON'
            )
        if 'query_id' in _dict:
            args['query_id'] = _dict.get('query_id')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'environment_id') and self.environment_id is not None:
            _dict['environment_id'] = self.environment_id
        if hasattr(self, 'session_token') and self.session_token is not None:
            _dict['session_token'] = self.session_token
        if hasattr(self,
                   'client_timestamp') and self.client_timestamp is not None:
            _dict['client_timestamp'] = datetime_to_string(
                self.client_timestamp)
        if hasattr(self, 'display_rank') and self.display_rank is not None:
            _dict['display_rank'] = self.display_rank
        if hasattr(self, 'collection_id') and self.collection_id is not None:
            _dict['collection_id'] = self.collection_id
        if hasattr(self, 'document_id') and self.document_id is not None:
            _dict['document_id'] = self.document_id
        if hasattr(self, 'query_id') and self.query_id is not None:
            _dict['query_id'] = self.query_id
        return _dict

    def __str__(self):
        """Return a `str` version of this EventData object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Expansion(object):
    """
    An expansion definition. Each object respresents one set of expandable strings. For
    example, you could have expansions for the word `hot` in one object, and expansions
    for the word `cold` in another.

    :attr list[str] input_terms: (optional) A list of terms that will be expanded for this
    expansion. If specified, only the items in this list are expanded.
    :attr list[str] expanded_terms: A list of terms that this expansion will be expanded
    to. If specified without **input_terms**, it also functions as the input term list.
    """

    def __init__(self, expanded_terms, input_terms=None):
        """
        Initialize a Expansion object.

        :param list[str] expanded_terms: A list of terms that this expansion will be
        expanded to. If specified without **input_terms**, it also functions as the input
        term list.
        :param list[str] input_terms: (optional) A list of terms that will be expanded for
        this expansion. If specified, only the items in this list are expanded.
        """
        self.input_terms = input_terms
        self.expanded_terms = expanded_terms

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Expansion object from a json dictionary."""
        args = {}
        if 'input_terms' in _dict:
            args['input_terms'] = _dict.get('input_terms')
        if 'expanded_terms' in _dict:
            args['expanded_terms'] = _dict.get('expanded_terms')
        else:
            raise ValueError(
                'Required property \'expanded_terms\' not present in Expansion JSON'
            )
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'input_terms') and self.input_terms is not None:
            _dict['input_terms'] = self.input_terms
        if hasattr(self, 'expanded_terms') and self.expanded_terms is not None:
            _dict['expanded_terms'] = self.expanded_terms
        return _dict

    def __str__(self):
        """Return a `str` version of this Expansion object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Expansions(object):
    """
    The query expansion definitions for the specified collection.

    :attr list[Expansion] expansions: An array of query expansion definitions.
     Each object in the **expansions** array represents a term or set of terms that will
    be expanded into other terms. Each expansion object can be configured as bidirectional
    or unidirectional. Bidirectional means that all terms are expanded to all other terms
    in the object. Unidirectional means that a set list of terms can be expanded into a
    second list of terms.
     To create a bi-directional expansion specify an **expanded_terms** array. When found
    in a query, all items in the **expanded_terms** array are then expanded to the other
    items in the same array.
     To create a uni-directional expansion, specify both an array of **input_terms** and
    an array of **expanded_terms**. When items in the **input_terms** array are present in
    a query, they are expanded using the items listed in the **expanded_terms** array.
    """

    def __init__(self, expansions):
        """
        Initialize a Expansions object.

        :param list[Expansion] expansions: An array of query expansion definitions.
         Each object in the **expansions** array represents a term or set of terms that
        will be expanded into other terms. Each expansion object can be configured as
        bidirectional or unidirectional. Bidirectional means that all terms are expanded
        to all other terms in the object. Unidirectional means that a set list of terms
        can be expanded into a second list of terms.
         To create a bi-directional expansion specify an **expanded_terms** array. When
        found in a query, all items in the **expanded_terms** array are then expanded to
        the other items in the same array.
         To create a uni-directional expansion, specify both an array of **input_terms**
        and an array of **expanded_terms**. When items in the **input_terms** array are
        present in a query, they are expanded using the items listed in the
        **expanded_terms** array.
        """
        self.expansions = expansions

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Expansions object from a json dictionary."""
        args = {}
        if 'expansions' in _dict:
            args['expansions'] = [
                Expansion._from_dict(x) for x in (_dict.get('expansions'))
            ]
        else:
            raise ValueError(
                'Required property \'expansions\' not present in Expansions JSON'
            )
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'expansions') and self.expansions is not None:
            _dict['expansions'] = [x._to_dict() for x in self.expansions]
        return _dict

    def __str__(self):
        """Return a `str` version of this Expansions object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Field(object):
    """
    Field.

    :attr str field_name: (optional) The name of the field.
    :attr str field_type: (optional) The type of the field.
    """

    def __init__(self, field_name=None, field_type=None):
        """
        Initialize a Field object.

        :param str field_name: (optional) The name of the field.
        :param str field_type: (optional) The type of the field.
        """
        self.field_name = field_name
        self.field_type = field_type

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Field object from a json dictionary."""
        args = {}
        if 'field' in _dict or 'field_name' in _dict:
            args['field_name'] = _dict.get('field') or _dict.get('field_name')
        if 'type' in _dict or 'field_type' in _dict:
            args['field_type'] = _dict.get('type') or _dict.get('field_type')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'field_name') and self.field_name is not None:
            _dict['field'] = self.field_name
        if hasattr(self, 'field_type') and self.field_type is not None:
            _dict['type'] = self.field_type
        return _dict

    def __str__(self):
        """Return a `str` version of this Field object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Filter(object):
    """
    Filter.

    :attr str match: (optional) The match the aggregated results queried for.
    """

    def __init__(self,
                 type=None,
                 results=None,
                 matching_results=None,
                 aggregations=None,
                 match=None):
        """
        Initialize a Filter object.

        :param str type: (optional) The type of aggregation command used. For example:
        term, filter, max, min, etc.
        :param list[AggregationResult] results: (optional) Array of aggregation results.
        :param int matching_results: (optional) Number of matching results.
        :param list[QueryAggregation] aggregations: (optional) Aggregations returned by
        the Discovery service.
        :param str match: (optional) The match the aggregated results queried for.
        """
        self.match = match

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Filter object from a json dictionary."""
        args = {}
        if 'match' in _dict:
            args['match'] = _dict.get('match')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'match') and self.match is not None:
            _dict['match'] = self.match
        return _dict

    def __str__(self):
        """Return a `str` version of this Filter object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class FontSetting(object):
    """
    FontSetting.

    :attr int level: (optional) The HTML heading level that any content with the matching
    font will be converted to.
    :attr int min_size: (optional) The minimum size of the font to match.
    :attr int max_size: (optional) The maximum size of the font to match.
    :attr bool bold: (optional) When `true`, the font is matched if it is bold.
    :attr bool italic: (optional) When `true`, the font is matched if it is italic.
    :attr str name: (optional) The name of the font.
    """

    def __init__(self,
                 level=None,
                 min_size=None,
                 max_size=None,
                 bold=None,
                 italic=None,
                 name=None):
        """
        Initialize a FontSetting object.

        :param int level: (optional) The HTML heading level that any content with the
        matching font will be converted to.
        :param int min_size: (optional) The minimum size of the font to match.
        :param int max_size: (optional) The maximum size of the font to match.
        :param bool bold: (optional) When `true`, the font is matched if it is bold.
        :param bool italic: (optional) When `true`, the font is matched if it is italic.
        :param str name: (optional) The name of the font.
        """
        self.level = level
        self.min_size = min_size
        self.max_size = max_size
        self.bold = bold
        self.italic = italic
        self.name = name

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a FontSetting object from a json dictionary."""
        args = {}
        if 'level' in _dict:
            args['level'] = _dict.get('level')
        if 'min_size' in _dict:
            args['min_size'] = _dict.get('min_size')
        if 'max_size' in _dict:
            args['max_size'] = _dict.get('max_size')
        if 'bold' in _dict:
            args['bold'] = _dict.get('bold')
        if 'italic' in _dict:
            args['italic'] = _dict.get('italic')
        if 'name' in _dict:
            args['name'] = _dict.get('name')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'level') and self.level is not None:
            _dict['level'] = self.level
        if hasattr(self, 'min_size') and self.min_size is not None:
            _dict['min_size'] = self.min_size
        if hasattr(self, 'max_size') and self.max_size is not None:
            _dict['max_size'] = self.max_size
        if hasattr(self, 'bold') and self.bold is not None:
            _dict['bold'] = self.bold
        if hasattr(self, 'italic') and self.italic is not None:
            _dict['italic'] = self.italic
        if hasattr(self, 'name') and self.name is not None:
            _dict['name'] = self.name
        return _dict

    def __str__(self):
        """Return a `str` version of this FontSetting object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Gateway(object):
    """
    Object describing a specific gateway.

    :attr str gateway_id: (optional) The gateway ID of the gateway.
    :attr str name: (optional) The user defined name of the gateway.
    :attr str status: (optional) The current status of the gateway. `connected` means the
    gateway is connected to the remotly installed gateway. `idle` means this gateway is
    not currently in use.
    :attr str token: (optional) The generated **token** for this gateway. The value of
    this field is used when configuring the remotly installed gateway.
    :attr str token_id: (optional) The generated **token_id** for this gateway. The value
    of this field is used when configuring the remotly installed gateway.
    """

    def __init__(self,
                 gateway_id=None,
                 name=None,
                 status=None,
                 token=None,
                 token_id=None):
        """
        Initialize a Gateway object.

        :param str gateway_id: (optional) The gateway ID of the gateway.
        :param str name: (optional) The user defined name of the gateway.
        :param str status: (optional) The current status of the gateway. `connected` means
        the gateway is connected to the remotly installed gateway. `idle` means this
        gateway is not currently in use.
        :param str token: (optional) The generated **token** for this gateway. The value
        of this field is used when configuring the remotly installed gateway.
        :param str token_id: (optional) The generated **token_id** for this gateway. The
        value of this field is used when configuring the remotly installed gateway.
        """
        self.gateway_id = gateway_id
        self.name = name
        self.status = status
        self.token = token
        self.token_id = token_id

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Gateway object from a json dictionary."""
        args = {}
        if 'gateway_id' in _dict:
            args['gateway_id'] = _dict.get('gateway_id')
        if 'name' in _dict:
            args['name'] = _dict.get('name')
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        if 'token' in _dict:
            args['token'] = _dict.get('token')
        if 'token_id' in _dict:
            args['token_id'] = _dict.get('token_id')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'gateway_id') and self.gateway_id is not None:
            _dict['gateway_id'] = self.gateway_id
        if hasattr(self, 'name') and self.name is not None:
            _dict['name'] = self.name
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        if hasattr(self, 'token') and self.token is not None:
            _dict['token'] = self.token
        if hasattr(self, 'token_id') and self.token_id is not None:
            _dict['token_id'] = self.token_id
        return _dict

    def __str__(self):
        """Return a `str` version of this Gateway object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class GatewayDelete(object):
    """
    Gatway deletion confirmation.

    :attr str gateway_id: (optional) The gateway ID of the deleted gateway.
    :attr str status: (optional) The status of the request.
    """

    def __init__(self, gateway_id=None, status=None):
        """
        Initialize a GatewayDelete object.

        :param str gateway_id: (optional) The gateway ID of the deleted gateway.
        :param str status: (optional) The status of the request.
        """
        self.gateway_id = gateway_id
        self.status = status

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a GatewayDelete object from a json dictionary."""
        args = {}
        if 'gateway_id' in _dict:
            args['gateway_id'] = _dict.get('gateway_id')
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'gateway_id') and self.gateway_id is not None:
            _dict['gateway_id'] = self.gateway_id
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        return _dict

    def __str__(self):
        """Return a `str` version of this GatewayDelete object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class GatewayList(object):
    """
    Object containing gateways array.

    :attr list[Gateway] gateways: (optional) Array of configured gateway connections.
    """

    def __init__(self, gateways=None):
        """
        Initialize a GatewayList object.

        :param list[Gateway] gateways: (optional) Array of configured gateway connections.
        """
        self.gateways = gateways

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a GatewayList object from a json dictionary."""
        args = {}
        if 'gateways' in _dict:
            args['gateways'] = [
                Gateway._from_dict(x) for x in (_dict.get('gateways'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'gateways') and self.gateways is not None:
            _dict['gateways'] = [x._to_dict() for x in self.gateways]
        return _dict

    def __str__(self):
        """Return a `str` version of this GatewayList object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Histogram(object):
    """
    Histogram.

    :attr str field: (optional) The field where the aggregation is located in the
    document.
    :attr int interval: (optional) Interval of the aggregation. (For 'histogram' type).
    """

    def __init__(self,
                 type=None,
                 results=None,
                 matching_results=None,
                 aggregations=None,
                 field=None,
                 interval=None):
        """
        Initialize a Histogram object.

        :param str type: (optional) The type of aggregation command used. For example:
        term, filter, max, min, etc.
        :param list[AggregationResult] results: (optional) Array of aggregation results.
        :param int matching_results: (optional) Number of matching results.
        :param list[QueryAggregation] aggregations: (optional) Aggregations returned by
        the Discovery service.
        :param str field: (optional) The field where the aggregation is located in the
        document.
        :param int interval: (optional) Interval of the aggregation. (For 'histogram'
        type).
        """
        self.field = field
        self.interval = interval

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Histogram object from a json dictionary."""
        args = {}
        if 'field' in _dict:
            args['field'] = _dict.get('field')
        if 'interval' in _dict:
            args['interval'] = _dict.get('interval')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'field') and self.field is not None:
            _dict['field'] = self.field
        if hasattr(self, 'interval') and self.interval is not None:
            _dict['interval'] = self.interval
        return _dict

    def __str__(self):
        """Return a `str` version of this Histogram object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class HtmlSettings(object):
    """
    A list of HTML conversion settings.

    :attr list[str] exclude_tags_completely: (optional) Array of HTML tags that are
    excluded completely.
    :attr list[str] exclude_tags_keep_content: (optional) Array of HTML tags which are
    excluded but still retain content.
    :attr XPathPatterns keep_content: (optional)
    :attr XPathPatterns exclude_content: (optional)
    :attr list[str] keep_tag_attributes: (optional) An array of HTML tag attributes to
    keep in the converted document.
    :attr list[str] exclude_tag_attributes: (optional) Array of HTML tag attributes to
    exclude.
    """

    def __init__(self,
                 exclude_tags_completely=None,
                 exclude_tags_keep_content=None,
                 keep_content=None,
                 exclude_content=None,
                 keep_tag_attributes=None,
                 exclude_tag_attributes=None):
        """
        Initialize a HtmlSettings object.

        :param list[str] exclude_tags_completely: (optional) Array of HTML tags that are
        excluded completely.
        :param list[str] exclude_tags_keep_content: (optional) Array of HTML tags which
        are excluded but still retain content.
        :param XPathPatterns keep_content: (optional)
        :param XPathPatterns exclude_content: (optional)
        :param list[str] keep_tag_attributes: (optional) An array of HTML tag attributes
        to keep in the converted document.
        :param list[str] exclude_tag_attributes: (optional) Array of HTML tag attributes
        to exclude.
        """
        self.exclude_tags_completely = exclude_tags_completely
        self.exclude_tags_keep_content = exclude_tags_keep_content
        self.keep_content = keep_content
        self.exclude_content = exclude_content
        self.keep_tag_attributes = keep_tag_attributes
        self.exclude_tag_attributes = exclude_tag_attributes

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a HtmlSettings object from a json dictionary."""
        args = {}
        if 'exclude_tags_completely' in _dict:
            args['exclude_tags_completely'] = _dict.get(
                'exclude_tags_completely')
        if 'exclude_tags_keep_content' in _dict:
            args['exclude_tags_keep_content'] = _dict.get(
                'exclude_tags_keep_content')
        if 'keep_content' in _dict:
            args['keep_content'] = XPathPatterns._from_dict(
                _dict.get('keep_content'))
        if 'exclude_content' in _dict:
            args['exclude_content'] = XPathPatterns._from_dict(
                _dict.get('exclude_content'))
        if 'keep_tag_attributes' in _dict:
            args['keep_tag_attributes'] = _dict.get('keep_tag_attributes')
        if 'exclude_tag_attributes' in _dict:
            args['exclude_tag_attributes'] = _dict.get('exclude_tag_attributes')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'exclude_tags_completely'
                  ) and self.exclude_tags_completely is not None:
            _dict['exclude_tags_completely'] = self.exclude_tags_completely
        if hasattr(self, 'exclude_tags_keep_content'
                  ) and self.exclude_tags_keep_content is not None:
            _dict['exclude_tags_keep_content'] = self.exclude_tags_keep_content
        if hasattr(self, 'keep_content') and self.keep_content is not None:
            _dict['keep_content'] = self.keep_content._to_dict()
        if hasattr(self,
                   'exclude_content') and self.exclude_content is not None:
            _dict['exclude_content'] = self.exclude_content._to_dict()
        if hasattr(
                self,
                'keep_tag_attributes') and self.keep_tag_attributes is not None:
            _dict['keep_tag_attributes'] = self.keep_tag_attributes
        if hasattr(self, 'exclude_tag_attributes'
                  ) and self.exclude_tag_attributes is not None:
            _dict['exclude_tag_attributes'] = self.exclude_tag_attributes
        return _dict

    def __str__(self):
        """Return a `str` version of this HtmlSettings object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class IndexCapacity(object):
    """
    Details about the resource usage and capacity of the environment.

    :attr EnvironmentDocuments documents: (optional) Summary of the document usage
    statistics for the environment.
    :attr DiskUsage disk_usage: (optional) Summary of the disk usage statistics for the
    environment.
    :attr CollectionUsage collections: (optional) Summary of the collection usage in the
    environment.
    """

    def __init__(self, documents=None, disk_usage=None, collections=None):
        """
        Initialize a IndexCapacity object.

        :param EnvironmentDocuments documents: (optional) Summary of the document usage
        statistics for the environment.
        :param DiskUsage disk_usage: (optional) Summary of the disk usage statistics for
        the environment.
        :param CollectionUsage collections: (optional) Summary of the collection usage in
        the environment.
        """
        self.documents = documents
        self.disk_usage = disk_usage
        self.collections = collections

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a IndexCapacity object from a json dictionary."""
        args = {}
        if 'documents' in _dict:
            args['documents'] = EnvironmentDocuments._from_dict(
                _dict.get('documents'))
        if 'disk_usage' in _dict:
            args['disk_usage'] = DiskUsage._from_dict(_dict.get('disk_usage'))
        if 'collections' in _dict:
            args['collections'] = CollectionUsage._from_dict(
                _dict.get('collections'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'documents') and self.documents is not None:
            _dict['documents'] = self.documents._to_dict()
        if hasattr(self, 'disk_usage') and self.disk_usage is not None:
            _dict['disk_usage'] = self.disk_usage._to_dict()
        if hasattr(self, 'collections') and self.collections is not None:
            _dict['collections'] = self.collections._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this IndexCapacity object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class ListCollectionFieldsResponse(object):
    """
    The list of fetched fields.
    The fields are returned using a fully qualified name format, however, the format
    differs slightly from that used by the query operations.
      * Fields which contain nested JSON objects are assigned a type of "nested".
      * Fields which belong to a nested object are prefixed with `.properties` (for
    example, `warnings.properties.severity` means that the `warnings` object has a
    property called `severity`).
      * Fields returned from the News collection are prefixed with
    `v{N}-fullnews-t3-{YEAR}.mappings` (for example,
    `v5-fullnews-t3-2016.mappings.text.properties.author`).

    :attr list[Field] fields: (optional) An array containing information about each field
    in the collections.
    """

    def __init__(self, fields=None):
        """
        Initialize a ListCollectionFieldsResponse object.

        :param list[Field] fields: (optional) An array containing information about each
        field in the collections.
        """
        self.fields = fields

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a ListCollectionFieldsResponse object from a json dictionary."""
        args = {}
        if 'fields' in _dict:
            args['fields'] = [
                Field._from_dict(x) for x in (_dict.get('fields'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'fields') and self.fields is not None:
            _dict['fields'] = [x._to_dict() for x in self.fields]
        return _dict

    def __str__(self):
        """Return a `str` version of this ListCollectionFieldsResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class ListCollectionsResponse(object):
    """
    ListCollectionsResponse.

    :attr list[Collection] collections: (optional) An array containing information about
    each collection in the environment.
    """

    def __init__(self, collections=None):
        """
        Initialize a ListCollectionsResponse object.

        :param list[Collection] collections: (optional) An array containing information
        about each collection in the environment.
        """
        self.collections = collections

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a ListCollectionsResponse object from a json dictionary."""
        args = {}
        if 'collections' in _dict:
            args['collections'] = [
                Collection._from_dict(x) for x in (_dict.get('collections'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'collections') and self.collections is not None:
            _dict['collections'] = [x._to_dict() for x in self.collections]
        return _dict

    def __str__(self):
        """Return a `str` version of this ListCollectionsResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class ListConfigurationsResponse(object):
    """
    ListConfigurationsResponse.

    :attr list[Configuration] configurations: (optional) An array of Configurations that
    are available for the service instance.
    """

    def __init__(self, configurations=None):
        """
        Initialize a ListConfigurationsResponse object.

        :param list[Configuration] configurations: (optional) An array of Configurations
        that are available for the service instance.
        """
        self.configurations = configurations

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a ListConfigurationsResponse object from a json dictionary."""
        args = {}
        if 'configurations' in _dict:
            args['configurations'] = [
                Configuration._from_dict(x)
                for x in (_dict.get('configurations'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'configurations') and self.configurations is not None:
            _dict['configurations'] = [
                x._to_dict() for x in self.configurations
            ]
        return _dict

    def __str__(self):
        """Return a `str` version of this ListConfigurationsResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class ListEnvironmentsResponse(object):
    """
    ListEnvironmentsResponse.

    :attr list[Environment] environments: (optional) An array of [environments] that are
    available for the service instance.
    """

    def __init__(self, environments=None):
        """
        Initialize a ListEnvironmentsResponse object.

        :param list[Environment] environments: (optional) An array of [environments] that
        are available for the service instance.
        """
        self.environments = environments

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a ListEnvironmentsResponse object from a json dictionary."""
        args = {}
        if 'environments' in _dict:
            args['environments'] = [
                Environment._from_dict(x) for x in (_dict.get('environments'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'environments') and self.environments is not None:
            _dict['environments'] = [x._to_dict() for x in self.environments]
        return _dict

    def __str__(self):
        """Return a `str` version of this ListEnvironmentsResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class LogQueryResponse(object):
    """
    Object containing results that match the requested **logs** query.

    :attr int matching_results: (optional) Number of matching results.
    :attr list[LogQueryResponseResult] results: (optional) Array of log query response
    results.
    """

    def __init__(self, matching_results=None, results=None):
        """
        Initialize a LogQueryResponse object.

        :param int matching_results: (optional) Number of matching results.
        :param list[LogQueryResponseResult] results: (optional) Array of log query
        response results.
        """
        self.matching_results = matching_results
        self.results = results

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a LogQueryResponse object from a json dictionary."""
        args = {}
        if 'matching_results' in _dict:
            args['matching_results'] = _dict.get('matching_results')
        if 'results' in _dict:
            args['results'] = [
                LogQueryResponseResult._from_dict(x)
                for x in (_dict.get('results'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self,
                   'matching_results') and self.matching_results is not None:
            _dict['matching_results'] = self.matching_results
        if hasattr(self, 'results') and self.results is not None:
            _dict['results'] = [x._to_dict() for x in self.results]
        return _dict

    def __str__(self):
        """Return a `str` version of this LogQueryResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class LogQueryResponseResult(object):
    """
    Individual result object for a **logs** query. Each object represents either a query
    to a Discovery collection or an event that is associated with a query.

    :attr str environment_id: (optional) The environment ID that is associated with this
    log entry.
    :attr str customer_id: (optional) The **customer_id** label that was specified in the
    header of the query or event API call that corresponds to this log entry.
    :attr str document_type: (optional) The type of log entry returned.
     **query** indicates that the log represents the results of a call to the single
    collection **query** method.
     **event** indicates that the log represents  a call to the **events** API.
    :attr str natural_language_query: (optional) The value of the
    **natural_language_query** query parameter that was used to create these results. Only
    returned with logs of type **query**.
    **Note:** Other query parameters (such as **filter** or **deduplicate**) might  have
    been used with this query, but are not recorded.
    :attr LogQueryResponseResultDocuments document_results: (optional) Object containing
    result information that was returned by the query used to create this log entry. Only
    returned with logs of type `query`.
    :attr datetime created_timestamp: (optional) Date that the log result was created.
    Returned in `YYYY-MM-DDThh:mm:ssZ` format.
    :attr datetime client_timestamp: (optional) Date specified by the user when recording
    an event. Returned in `YYYY-MM-DDThh:mm:ssZ` format. Only returned with logs of type
    **event**.
    :attr str query_id: (optional) Identifier that corresponds to the
    **natural_language_query** string used in the original or associated query. All
    **event** and **query** log entries that have the same original
    **natural_language_query** string also have them same **query_id**. This field can be
    used to recall all **event** and **query** log results that have the same original
    query (**event** logs do not contain the original **natural_language_query** field).
    :attr str session_token: (optional) Unique identifier (within a 24-hour period) that
    identifies a single `query` log and any `event` logs that were created for it.
    **Note:** If the exact same query is run at the exact same time on different days, the
    **session_token** for those queries might be identical. However, the
    **created_timestamp** differs.
    **Note:** Session tokens are case sensitive. To avoid matching on session tokens that
    are identical except for case, use the exact match operator (`::`) when you query for
    a specific session token.
    :attr str collection_id: (optional) The collection ID of the document associated with
    this event. Only returned with logs of type `event`.
    :attr int display_rank: (optional) The original display rank of the document
    associated with this event. Only returned with logs of type `event`.
    :attr str document_id: (optional) The document ID of the document associated with this
    event. Only returned with logs of type `event`.
    :attr str event_type: (optional) The type of event that this object respresents.
    Possible values are
     -  `query` the log of a query to a collection
     -  `click` the result of a call to the **events** endpoint.
    :attr str result_type: (optional) The type of result that this **event** is associated
    with. Only returned with logs of type `event`.
    """

    def __init__(self,
                 environment_id=None,
                 customer_id=None,
                 document_type=None,
                 natural_language_query=None,
                 document_results=None,
                 created_timestamp=None,
                 client_timestamp=None,
                 query_id=None,
                 session_token=None,
                 collection_id=None,
                 display_rank=None,
                 document_id=None,
                 event_type=None,
                 result_type=None):
        """
        Initialize a LogQueryResponseResult object.

        :param str environment_id: (optional) The environment ID that is associated with
        this log entry.
        :param str customer_id: (optional) The **customer_id** label that was specified in
        the header of the query or event API call that corresponds to this log entry.
        :param str document_type: (optional) The type of log entry returned.
         **query** indicates that the log represents the results of a call to the single
        collection **query** method.
         **event** indicates that the log represents  a call to the **events** API.
        :param str natural_language_query: (optional) The value of the
        **natural_language_query** query parameter that was used to create these results.
        Only returned with logs of type **query**.
        **Note:** Other query parameters (such as **filter** or **deduplicate**) might
        have been used with this query, but are not recorded.
        :param LogQueryResponseResultDocuments document_results: (optional) Object
        containing result information that was returned by the query used to create this
        log entry. Only returned with logs of type `query`.
        :param datetime created_timestamp: (optional) Date that the log result was
        created. Returned in `YYYY-MM-DDThh:mm:ssZ` format.
        :param datetime client_timestamp: (optional) Date specified by the user when
        recording an event. Returned in `YYYY-MM-DDThh:mm:ssZ` format. Only returned with
        logs of type **event**.
        :param str query_id: (optional) Identifier that corresponds to the
        **natural_language_query** string used in the original or associated query. All
        **event** and **query** log entries that have the same original
        **natural_language_query** string also have them same **query_id**. This field can
        be used to recall all **event** and **query** log results that have the same
        original query (**event** logs do not contain the original
        **natural_language_query** field).
        :param str session_token: (optional) Unique identifier (within a 24-hour period)
        that identifies a single `query` log and any `event` logs that were created for
        it.
        **Note:** If the exact same query is run at the exact same time on different days,
        the **session_token** for those queries might be identical. However, the
        **created_timestamp** differs.
        **Note:** Session tokens are case sensitive. To avoid matching on session tokens
        that are identical except for case, use the exact match operator (`::`) when you
        query for a specific session token.
        :param str collection_id: (optional) The collection ID of the document associated
        with this event. Only returned with logs of type `event`.
        :param int display_rank: (optional) The original display rank of the document
        associated with this event. Only returned with logs of type `event`.
        :param str document_id: (optional) The document ID of the document associated with
        this event. Only returned with logs of type `event`.
        :param str event_type: (optional) The type of event that this object respresents.
        Possible values are
         -  `query` the log of a query to a collection
         -  `click` the result of a call to the **events** endpoint.
        :param str result_type: (optional) The type of result that this **event** is
        associated with. Only returned with logs of type `event`.
        """
        self.environment_id = environment_id
        self.customer_id = customer_id
        self.document_type = document_type
        self.natural_language_query = natural_language_query
        self.document_results = document_results
        self.created_timestamp = created_timestamp
        self.client_timestamp = client_timestamp
        self.query_id = query_id
        self.session_token = session_token
        self.collection_id = collection_id
        self.display_rank = display_rank
        self.document_id = document_id
        self.event_type = event_type
        self.result_type = result_type

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a LogQueryResponseResult object from a json dictionary."""
        args = {}
        if 'environment_id' in _dict:
            args['environment_id'] = _dict.get('environment_id')
        if 'customer_id' in _dict:
            args['customer_id'] = _dict.get('customer_id')
        if 'document_type' in _dict:
            args['document_type'] = _dict.get('document_type')
        if 'natural_language_query' in _dict:
            args['natural_language_query'] = _dict.get('natural_language_query')
        if 'document_results' in _dict:
            args[
                'document_results'] = LogQueryResponseResultDocuments._from_dict(
                    _dict.get('document_results'))
        if 'created_timestamp' in _dict:
            args['created_timestamp'] = string_to_datetime(
                _dict.get('created_timestamp'))
        if 'client_timestamp' in _dict:
            args['client_timestamp'] = string_to_datetime(
                _dict.get('client_timestamp'))
        if 'query_id' in _dict:
            args['query_id'] = _dict.get('query_id')
        if 'session_token' in _dict:
            args['session_token'] = _dict.get('session_token')
        if 'collection_id' in _dict:
            args['collection_id'] = _dict.get('collection_id')
        if 'display_rank' in _dict:
            args['display_rank'] = _dict.get('display_rank')
        if 'document_id' in _dict:
            args['document_id'] = _dict.get('document_id')
        if 'event_type' in _dict:
            args['event_type'] = _dict.get('event_type')
        if 'result_type' in _dict:
            args['result_type'] = _dict.get('result_type')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'environment_id') and self.environment_id is not None:
            _dict['environment_id'] = self.environment_id
        if hasattr(self, 'customer_id') and self.customer_id is not None:
            _dict['customer_id'] = self.customer_id
        if hasattr(self, 'document_type') and self.document_type is not None:
            _dict['document_type'] = self.document_type
        if hasattr(self, 'natural_language_query'
                  ) and self.natural_language_query is not None:
            _dict['natural_language_query'] = self.natural_language_query
        if hasattr(self,
                   'document_results') and self.document_results is not None:
            _dict['document_results'] = self.document_results._to_dict()
        if hasattr(self,
                   'created_timestamp') and self.created_timestamp is not None:
            _dict['created_timestamp'] = datetime_to_string(
                self.created_timestamp)
        if hasattr(self,
                   'client_timestamp') and self.client_timestamp is not None:
            _dict['client_timestamp'] = datetime_to_string(
                self.client_timestamp)
        if hasattr(self, 'query_id') and self.query_id is not None:
            _dict['query_id'] = self.query_id
        if hasattr(self, 'session_token') and self.session_token is not None:
            _dict['session_token'] = self.session_token
        if hasattr(self, 'collection_id') and self.collection_id is not None:
            _dict['collection_id'] = self.collection_id
        if hasattr(self, 'display_rank') and self.display_rank is not None:
            _dict['display_rank'] = self.display_rank
        if hasattr(self, 'document_id') and self.document_id is not None:
            _dict['document_id'] = self.document_id
        if hasattr(self, 'event_type') and self.event_type is not None:
            _dict['event_type'] = self.event_type
        if hasattr(self, 'result_type') and self.result_type is not None:
            _dict['result_type'] = self.result_type
        return _dict

    def __str__(self):
        """Return a `str` version of this LogQueryResponseResult object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class LogQueryResponseResultDocuments(object):
    """
    Object containing result information that was returned by the query used to create
    this log entry. Only returned with logs of type `query`.

    :attr list[LogQueryResponseResultDocumentsResult] results: (optional) Array of log
    query response results.
    :attr int count: (optional) The number of results returned in the query associate with
    this log.
    """

    def __init__(self, results=None, count=None):
        """
        Initialize a LogQueryResponseResultDocuments object.

        :param list[LogQueryResponseResultDocumentsResult] results: (optional) Array of
        log query response results.
        :param int count: (optional) The number of results returned in the query associate
        with this log.
        """
        self.results = results
        self.count = count

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a LogQueryResponseResultDocuments object from a json dictionary."""
        args = {}
        if 'results' in _dict:
            args['results'] = [
                LogQueryResponseResultDocumentsResult._from_dict(x)
                for x in (_dict.get('results'))
            ]
        if 'count' in _dict:
            args['count'] = _dict.get('count')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'results') and self.results is not None:
            _dict['results'] = [x._to_dict() for x in self.results]
        if hasattr(self, 'count') and self.count is not None:
            _dict['count'] = self.count
        return _dict

    def __str__(self):
        """Return a `str` version of this LogQueryResponseResultDocuments object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class LogQueryResponseResultDocumentsResult(object):
    """
    Each object in the **results** array corresponds to an individual document returned by
    the original query.

    :attr int position: (optional) The result rank of this document. A position of `1`
    indicates that it was the first returned result.
    :attr str document_id: (optional) The **document_id** of the document that this result
    represents.
    :attr float score: (optional) The raw score of this result. A higher score indicates a
    greater match to the query parameters.
    :attr float confidence: (optional) The confidence score of the result's analysis. A
    higher score indicating greater confidence.
    :attr str collection_id: (optional) The **collection_id** of the document represented
    by this result.
    """

    def __init__(self,
                 position=None,
                 document_id=None,
                 score=None,
                 confidence=None,
                 collection_id=None):
        """
        Initialize a LogQueryResponseResultDocumentsResult object.

        :param int position: (optional) The result rank of this document. A position of
        `1` indicates that it was the first returned result.
        :param str document_id: (optional) The **document_id** of the document that this
        result represents.
        :param float score: (optional) The raw score of this result. A higher score
        indicates a greater match to the query parameters.
        :param float confidence: (optional) The confidence score of the result's analysis.
        A higher score indicating greater confidence.
        :param str collection_id: (optional) The **collection_id** of the document
        represented by this result.
        """
        self.position = position
        self.document_id = document_id
        self.score = score
        self.confidence = confidence
        self.collection_id = collection_id

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a LogQueryResponseResultDocumentsResult object from a json dictionary."""
        args = {}
        if 'position' in _dict:
            args['position'] = _dict.get('position')
        if 'document_id' in _dict:
            args['document_id'] = _dict.get('document_id')
        if 'score' in _dict:
            args['score'] = _dict.get('score')
        if 'confidence' in _dict:
            args['confidence'] = _dict.get('confidence')
        if 'collection_id' in _dict:
            args['collection_id'] = _dict.get('collection_id')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'position') and self.position is not None:
            _dict['position'] = self.position
        if hasattr(self, 'document_id') and self.document_id is not None:
            _dict['document_id'] = self.document_id
        if hasattr(self, 'score') and self.score is not None:
            _dict['score'] = self.score
        if hasattr(self, 'confidence') and self.confidence is not None:
            _dict['confidence'] = self.confidence
        if hasattr(self, 'collection_id') and self.collection_id is not None:
            _dict['collection_id'] = self.collection_id
        return _dict

    def __str__(self):
        """Return a `str` version of this LogQueryResponseResultDocumentsResult object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MetricAggregation(object):
    """
    An aggregation analyzing log information for queries and events.

    :attr str interval: (optional) The measurement interval for this metric. Metric
    intervals are always 1 day (`1d`).
    :attr str event_type: (optional) The event type associated with this metric result.
    This field, when present, will always be `click`.
    :attr list[MetricAggregationResult] results: (optional) Array of metric aggregation
    query results.
    """

    def __init__(self, interval=None, event_type=None, results=None):
        """
        Initialize a MetricAggregation object.

        :param str interval: (optional) The measurement interval for this metric. Metric
        intervals are always 1 day (`1d`).
        :param str event_type: (optional) The event type associated with this metric
        result. This field, when present, will always be `click`.
        :param list[MetricAggregationResult] results: (optional) Array of metric
        aggregation query results.
        """
        self.interval = interval
        self.event_type = event_type
        self.results = results

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MetricAggregation object from a json dictionary."""
        args = {}
        if 'interval' in _dict:
            args['interval'] = _dict.get('interval')
        if 'event_type' in _dict:
            args['event_type'] = _dict.get('event_type')
        if 'results' in _dict:
            args['results'] = [
                MetricAggregationResult._from_dict(x)
                for x in (_dict.get('results'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'interval') and self.interval is not None:
            _dict['interval'] = self.interval
        if hasattr(self, 'event_type') and self.event_type is not None:
            _dict['event_type'] = self.event_type
        if hasattr(self, 'results') and self.results is not None:
            _dict['results'] = [x._to_dict() for x in self.results]
        return _dict

    def __str__(self):
        """Return a `str` version of this MetricAggregation object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MetricAggregationResult(object):
    """
    Aggregation result data for the requested metric.

    :attr datetime key_as_string: (optional) Date in string form representing the start of
    this interval.
    :attr int key: (optional) Unix epoch time equivalent of the **key_as_string**, that
    represents the start of this interval.
    :attr int matching_results: (optional) Number of matching results.
    :attr float event_rate: (optional) The number of queries with associated events
    divided by the total number of queries for the interval. Only returned with
    **event_rate** metrics.
    """

    def __init__(self,
                 key_as_string=None,
                 key=None,
                 matching_results=None,
                 event_rate=None):
        """
        Initialize a MetricAggregationResult object.

        :param datetime key_as_string: (optional) Date in string form representing the
        start of this interval.
        :param int key: (optional) Unix epoch time equivalent of the **key_as_string**,
        that represents the start of this interval.
        :param int matching_results: (optional) Number of matching results.
        :param float event_rate: (optional) The number of queries with associated events
        divided by the total number of queries for the interval. Only returned with
        **event_rate** metrics.
        """
        self.key_as_string = key_as_string
        self.key = key
        self.matching_results = matching_results
        self.event_rate = event_rate

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MetricAggregationResult object from a json dictionary."""
        args = {}
        if 'key_as_string' in _dict:
            args['key_as_string'] = string_to_datetime(
                _dict.get('key_as_string'))
        if 'key' in _dict:
            args['key'] = _dict.get('key')
        if 'matching_results' in _dict:
            args['matching_results'] = _dict.get('matching_results')
        if 'event_rate' in _dict:
            args['event_rate'] = _dict.get('event_rate')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'key_as_string') and self.key_as_string is not None:
            _dict['key_as_string'] = datetime_to_string(self.key_as_string)
        if hasattr(self, 'key') and self.key is not None:
            _dict['key'] = self.key
        if hasattr(self,
                   'matching_results') and self.matching_results is not None:
            _dict['matching_results'] = self.matching_results
        if hasattr(self, 'event_rate') and self.event_rate is not None:
            _dict['event_rate'] = self.event_rate
        return _dict

    def __str__(self):
        """Return a `str` version of this MetricAggregationResult object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MetricResponse(object):
    """
    The response generated from a call to a **metrics** method.

    :attr list[MetricAggregation] aggregations: (optional) Array of metric aggregations.
    """

    def __init__(self, aggregations=None):
        """
        Initialize a MetricResponse object.

        :param list[MetricAggregation] aggregations: (optional) Array of metric
        aggregations.
        """
        self.aggregations = aggregations

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MetricResponse object from a json dictionary."""
        args = {}
        if 'aggregations' in _dict:
            args['aggregations'] = [
                MetricAggregation._from_dict(x)
                for x in (_dict.get('aggregations'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'aggregations') and self.aggregations is not None:
            _dict['aggregations'] = [x._to_dict() for x in self.aggregations]
        return _dict

    def __str__(self):
        """Return a `str` version of this MetricResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MetricTokenAggregation(object):
    """
    An aggregation analyzing log information for queries and events.

    :attr str event_type: (optional) The event type associated with this metric result.
    This field, when present, will always be `click`.
    :attr list[MetricTokenAggregationResult] results: (optional) Array of results for the
    metric token aggregation.
    """

    def __init__(self, event_type=None, results=None):
        """
        Initialize a MetricTokenAggregation object.

        :param str event_type: (optional) The event type associated with this metric
        result. This field, when present, will always be `click`.
        :param list[MetricTokenAggregationResult] results: (optional) Array of results for
        the metric token aggregation.
        """
        self.event_type = event_type
        self.results = results

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MetricTokenAggregation object from a json dictionary."""
        args = {}
        if 'event_type' in _dict:
            args['event_type'] = _dict.get('event_type')
        if 'results' in _dict:
            args['results'] = [
                MetricTokenAggregationResult._from_dict(x)
                for x in (_dict.get('results'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'event_type') and self.event_type is not None:
            _dict['event_type'] = self.event_type
        if hasattr(self, 'results') and self.results is not None:
            _dict['results'] = [x._to_dict() for x in self.results]
        return _dict

    def __str__(self):
        """Return a `str` version of this MetricTokenAggregation object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MetricTokenAggregationResult(object):
    """
    Aggregation result data for the requested metric.

    :attr str key: (optional) The content of the **natural_language_query** parameter used
    in the query that this result represents.
    :attr int matching_results: (optional) Number of matching results.
    :attr float event_rate: (optional) The number of queries with associated events
    divided by the total number of queries currently stored (queries and events are stored
    in the log for 30 days).
    """

    def __init__(self, key=None, matching_results=None, event_rate=None):
        """
        Initialize a MetricTokenAggregationResult object.

        :param str key: (optional) The content of the **natural_language_query** parameter
        used in the query that this result represents.
        :param int matching_results: (optional) Number of matching results.
        :param float event_rate: (optional) The number of queries with associated events
        divided by the total number of queries currently stored (queries and events are
        stored in the log for 30 days).
        """
        self.key = key
        self.matching_results = matching_results
        self.event_rate = event_rate

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MetricTokenAggregationResult object from a json dictionary."""
        args = {}
        if 'key' in _dict:
            args['key'] = _dict.get('key')
        if 'matching_results' in _dict:
            args['matching_results'] = _dict.get('matching_results')
        if 'event_rate' in _dict:
            args['event_rate'] = _dict.get('event_rate')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'key') and self.key is not None:
            _dict['key'] = self.key
        if hasattr(self,
                   'matching_results') and self.matching_results is not None:
            _dict['matching_results'] = self.matching_results
        if hasattr(self, 'event_rate') and self.event_rate is not None:
            _dict['event_rate'] = self.event_rate
        return _dict

    def __str__(self):
        """Return a `str` version of this MetricTokenAggregationResult object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MetricTokenResponse(object):
    """
    The response generated from a call to a **metrics** method that evaluates tokens.

    :attr list[MetricTokenAggregation] aggregations: (optional) Array of metric token
    aggregations.
    """

    def __init__(self, aggregations=None):
        """
        Initialize a MetricTokenResponse object.

        :param list[MetricTokenAggregation] aggregations: (optional) Array of metric token
        aggregations.
        """
        self.aggregations = aggregations

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MetricTokenResponse object from a json dictionary."""
        args = {}
        if 'aggregations' in _dict:
            args['aggregations'] = [
                MetricTokenAggregation._from_dict(x)
                for x in (_dict.get('aggregations'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'aggregations') and self.aggregations is not None:
            _dict['aggregations'] = [x._to_dict() for x in self.aggregations]
        return _dict

    def __str__(self):
        """Return a `str` version of this MetricTokenResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Nested(object):
    """
    Nested.

    :attr str path: (optional) The area of the results the aggregation was restricted to.
    """

    def __init__(self,
                 type=None,
                 results=None,
                 matching_results=None,
                 aggregations=None,
                 path=None):
        """
        Initialize a Nested object.

        :param str type: (optional) The type of aggregation command used. For example:
        term, filter, max, min, etc.
        :param list[AggregationResult] results: (optional) Array of aggregation results.
        :param int matching_results: (optional) Number of matching results.
        :param list[QueryAggregation] aggregations: (optional) Aggregations returned by
        the Discovery service.
        :param str path: (optional) The area of the results the aggregation was restricted
        to.
        """
        self.path = path

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Nested object from a json dictionary."""
        args = {}
        if 'path' in _dict:
            args['path'] = _dict.get('path')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'path') and self.path is not None:
            _dict['path'] = self.path
        return _dict

    def __str__(self):
        """Return a `str` version of this Nested object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class NluEnrichmentCategories(object):
    """
    An object that indicates the Categories enrichment will be applied to the specified
    field.

    """

    def __init__(self, **kwargs):
        """
        Initialize a NluEnrichmentCategories object.

        :param **kwargs: (optional) Any additional properties.
        """
        for _key, _value in kwargs.items():
            setattr(self, _key, _value)

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a NluEnrichmentCategories object from a json dictionary."""
        args = {}
        xtra = _dict.copy()
        args.update(xtra)
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, '_additionalProperties'):
            for _key in self._additionalProperties:
                _value = getattr(self, _key, None)
                if _value is not None:
                    _dict[_key] = _value
        return _dict

    def __setattr__(self, name, value):
        properties = {}
        if not hasattr(self, '_additionalProperties'):
            super(NluEnrichmentCategories, self).__setattr__(
                '_additionalProperties', set())
        if name not in properties:
            self._additionalProperties.add(name)
        super(NluEnrichmentCategories, self).__setattr__(name, value)

    def __str__(self):
        """Return a `str` version of this NluEnrichmentCategories object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class NluEnrichmentConcepts(object):
    """
    An object specifiying the concepts enrichment and related parameters.

    :attr int limit: (optional) The maximum number of concepts enrichments to extact from
    each instance of the specified field.
    """

    def __init__(self, limit=None):
        """
        Initialize a NluEnrichmentConcepts object.

        :param int limit: (optional) The maximum number of concepts enrichments to extact
        from each instance of the specified field.
        """
        self.limit = limit

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a NluEnrichmentConcepts object from a json dictionary."""
        args = {}
        if 'limit' in _dict:
            args['limit'] = _dict.get('limit')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'limit') and self.limit is not None:
            _dict['limit'] = self.limit
        return _dict

    def __str__(self):
        """Return a `str` version of this NluEnrichmentConcepts object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class NluEnrichmentEmotion(object):
    """
    An object specifying the emotion detection enrichment and related parameters.

    :attr bool document: (optional) When `true`, emotion detection is performed on the
    entire field.
    :attr list[str] targets: (optional) A comma-separated list of target strings that will
    have any associated emotions detected.
    """

    def __init__(self, document=None, targets=None):
        """
        Initialize a NluEnrichmentEmotion object.

        :param bool document: (optional) When `true`, emotion detection is performed on
        the entire field.
        :param list[str] targets: (optional) A comma-separated list of target strings that
        will have any associated emotions detected.
        """
        self.document = document
        self.targets = targets

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a NluEnrichmentEmotion object from a json dictionary."""
        args = {}
        if 'document' in _dict:
            args['document'] = _dict.get('document')
        if 'targets' in _dict:
            args['targets'] = _dict.get('targets')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'document') and self.document is not None:
            _dict['document'] = self.document
        if hasattr(self, 'targets') and self.targets is not None:
            _dict['targets'] = self.targets
        return _dict

    def __str__(self):
        """Return a `str` version of this NluEnrichmentEmotion object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class NluEnrichmentEntities(object):
    """
    An object speficying the Entities enrichment and related parameters.

    :attr bool sentiment: (optional) When `true`, sentiment analysis of entities will be
    performed on the specified field.
    :attr bool emotion: (optional) When `true`, emotion detection of entities will be
    performed on the specified field.
    :attr int limit: (optional) The maximum number of entities to extract for each
    instance of the specified field.
    :attr bool mentions: (optional) When `true`, the number of mentions of each identified
    entity is recorded. The default is `false`.
    :attr bool mention_types: (optional) When `true`, the types of mentions for each
    idetifieid entity is recorded. The default is `false`.
    :attr bool sentence_locations: (optional) When `true`, a list of sentence locations
    for each instance of each identified entity is recorded. The default is `false`.
    :attr str model: (optional) The enrichement model to use with entity extraction. May
    be a custom model provided by Watson Knowledge Studio, the public model for use with
    Knowledge Graph `en-news`, or the default public model `alchemy`.
    """

    def __init__(self,
                 sentiment=None,
                 emotion=None,
                 limit=None,
                 mentions=None,
                 mention_types=None,
                 sentence_locations=None,
                 model=None):
        """
        Initialize a NluEnrichmentEntities object.

        :param bool sentiment: (optional) When `true`, sentiment analysis of entities will
        be performed on the specified field.
        :param bool emotion: (optional) When `true`, emotion detection of entities will be
        performed on the specified field.
        :param int limit: (optional) The maximum number of entities to extract for each
        instance of the specified field.
        :param bool mentions: (optional) When `true`, the number of mentions of each
        identified entity is recorded. The default is `false`.
        :param bool mention_types: (optional) When `true`, the types of mentions for each
        idetifieid entity is recorded. The default is `false`.
        :param bool sentence_locations: (optional) When `true`, a list of sentence
        locations for each instance of each identified entity is recorded. The default is
        `false`.
        :param str model: (optional) The enrichement model to use with entity extraction.
        May be a custom model provided by Watson Knowledge Studio, the public model for
        use with Knowledge Graph `en-news`, or the default public model `alchemy`.
        """
        self.sentiment = sentiment
        self.emotion = emotion
        self.limit = limit
        self.mentions = mentions
        self.mention_types = mention_types
        self.sentence_locations = sentence_locations
        self.model = model

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a NluEnrichmentEntities object from a json dictionary."""
        args = {}
        if 'sentiment' in _dict:
            args['sentiment'] = _dict.get('sentiment')
        if 'emotion' in _dict:
            args['emotion'] = _dict.get('emotion')
        if 'limit' in _dict:
            args['limit'] = _dict.get('limit')
        if 'mentions' in _dict:
            args['mentions'] = _dict.get('mentions')
        if 'mention_types' in _dict:
            args['mention_types'] = _dict.get('mention_types')
        if 'sentence_locations' in _dict:
            args['sentence_locations'] = _dict.get('sentence_locations')
        if 'model' in _dict:
            args['model'] = _dict.get('model')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'sentiment') and self.sentiment is not None:
            _dict['sentiment'] = self.sentiment
        if hasattr(self, 'emotion') and self.emotion is not None:
            _dict['emotion'] = self.emotion
        if hasattr(self, 'limit') and self.limit is not None:
            _dict['limit'] = self.limit
        if hasattr(self, 'mentions') and self.mentions is not None:
            _dict['mentions'] = self.mentions
        if hasattr(self, 'mention_types') and self.mention_types is not None:
            _dict['mention_types'] = self.mention_types
        if hasattr(
                self,
                'sentence_locations') and self.sentence_locations is not None:
            _dict['sentence_locations'] = self.sentence_locations
        if hasattr(self, 'model') and self.model is not None:
            _dict['model'] = self.model
        return _dict

    def __str__(self):
        """Return a `str` version of this NluEnrichmentEntities object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class NluEnrichmentFeatures(object):
    """
    NluEnrichmentFeatures.

    :attr NluEnrichmentKeywords keywords: (optional) An object specifying the Keyword
    enrichment and related parameters.
    :attr NluEnrichmentEntities entities: (optional) An object speficying the Entities
    enrichment and related parameters.
    :attr NluEnrichmentSentiment sentiment: (optional) An object specifying the sentiment
    extraction enrichment and related parameters.
    :attr NluEnrichmentEmotion emotion: (optional) An object specifying the emotion
    detection enrichment and related parameters.
    :attr NluEnrichmentCategories categories: (optional) An object that indicates the
    Categories enrichment will be applied to the specified field.
    :attr NluEnrichmentSemanticRoles semantic_roles: (optional) An object specifiying the
    semantic roles enrichment and related parameters.
    :attr NluEnrichmentRelations relations: (optional) An object specifying the relations
    enrichment and related parameters.
    :attr NluEnrichmentConcepts concepts: (optional) An object specifiying the concepts
    enrichment and related parameters.
    """

    def __init__(self,
                 keywords=None,
                 entities=None,
                 sentiment=None,
                 emotion=None,
                 categories=None,
                 semantic_roles=None,
                 relations=None,
                 concepts=None):
        """
        Initialize a NluEnrichmentFeatures object.

        :param NluEnrichmentKeywords keywords: (optional) An object specifying the Keyword
        enrichment and related parameters.
        :param NluEnrichmentEntities entities: (optional) An object speficying the
        Entities enrichment and related parameters.
        :param NluEnrichmentSentiment sentiment: (optional) An object specifying the
        sentiment extraction enrichment and related parameters.
        :param NluEnrichmentEmotion emotion: (optional) An object specifying the emotion
        detection enrichment and related parameters.
        :param NluEnrichmentCategories categories: (optional) An object that indicates the
        Categories enrichment will be applied to the specified field.
        :param NluEnrichmentSemanticRoles semantic_roles: (optional) An object specifiying
        the semantic roles enrichment and related parameters.
        :param NluEnrichmentRelations relations: (optional) An object specifying the
        relations enrichment and related parameters.
        :param NluEnrichmentConcepts concepts: (optional) An object specifiying the
        concepts enrichment and related parameters.
        """
        self.keywords = keywords
        self.entities = entities
        self.sentiment = sentiment
        self.emotion = emotion
        self.categories = categories
        self.semantic_roles = semantic_roles
        self.relations = relations
        self.concepts = concepts

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a NluEnrichmentFeatures object from a json dictionary."""
        args = {}
        if 'keywords' in _dict:
            args['keywords'] = NluEnrichmentKeywords._from_dict(
                _dict.get('keywords'))
        if 'entities' in _dict:
            args['entities'] = NluEnrichmentEntities._from_dict(
                _dict.get('entities'))
        if 'sentiment' in _dict:
            args['sentiment'] = NluEnrichmentSentiment._from_dict(
                _dict.get('sentiment'))
        if 'emotion' in _dict:
            args['emotion'] = NluEnrichmentEmotion._from_dict(
                _dict.get('emotion'))
        if 'categories' in _dict:
            args['categories'] = NluEnrichmentCategories._from_dict(
                _dict.get('categories'))
        if 'semantic_roles' in _dict:
            args['semantic_roles'] = NluEnrichmentSemanticRoles._from_dict(
                _dict.get('semantic_roles'))
        if 'relations' in _dict:
            args['relations'] = NluEnrichmentRelations._from_dict(
                _dict.get('relations'))
        if 'concepts' in _dict:
            args['concepts'] = NluEnrichmentConcepts._from_dict(
                _dict.get('concepts'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'keywords') and self.keywords is not None:
            _dict['keywords'] = self.keywords._to_dict()
        if hasattr(self, 'entities') and self.entities is not None:
            _dict['entities'] = self.entities._to_dict()
        if hasattr(self, 'sentiment') and self.sentiment is not None:
            _dict['sentiment'] = self.sentiment._to_dict()
        if hasattr(self, 'emotion') and self.emotion is not None:
            _dict['emotion'] = self.emotion._to_dict()
        if hasattr(self, 'categories') and self.categories is not None:
            _dict['categories'] = self.categories._to_dict()
        if hasattr(self, 'semantic_roles') and self.semantic_roles is not None:
            _dict['semantic_roles'] = self.semantic_roles._to_dict()
        if hasattr(self, 'relations') and self.relations is not None:
            _dict['relations'] = self.relations._to_dict()
        if hasattr(self, 'concepts') and self.concepts is not None:
            _dict['concepts'] = self.concepts._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this NluEnrichmentFeatures object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class NluEnrichmentKeywords(object):
    """
    An object specifying the Keyword enrichment and related parameters.

    :attr bool sentiment: (optional) When `true`, sentiment analysis of keywords will be
    performed on the specified field.
    :attr bool emotion: (optional) When `true`, emotion detection of keywords will be
    performed on the specified field.
    :attr int limit: (optional) The maximum number of keywords to extract for each
    instance of the specified field.
    """

    def __init__(self, sentiment=None, emotion=None, limit=None):
        """
        Initialize a NluEnrichmentKeywords object.

        :param bool sentiment: (optional) When `true`, sentiment analysis of keywords will
        be performed on the specified field.
        :param bool emotion: (optional) When `true`, emotion detection of keywords will be
        performed on the specified field.
        :param int limit: (optional) The maximum number of keywords to extract for each
        instance of the specified field.
        """
        self.sentiment = sentiment
        self.emotion = emotion
        self.limit = limit

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a NluEnrichmentKeywords object from a json dictionary."""
        args = {}
        if 'sentiment' in _dict:
            args['sentiment'] = _dict.get('sentiment')
        if 'emotion' in _dict:
            args['emotion'] = _dict.get('emotion')
        if 'limit' in _dict:
            args['limit'] = _dict.get('limit')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'sentiment') and self.sentiment is not None:
            _dict['sentiment'] = self.sentiment
        if hasattr(self, 'emotion') and self.emotion is not None:
            _dict['emotion'] = self.emotion
        if hasattr(self, 'limit') and self.limit is not None:
            _dict['limit'] = self.limit
        return _dict

    def __str__(self):
        """Return a `str` version of this NluEnrichmentKeywords object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class NluEnrichmentRelations(object):
    """
    An object specifying the relations enrichment and related parameters.

    :attr str model: (optional) *For use with `natural_language_understanding` enrichments
    only.* The enrichement model to use with relationship extraction. May be a custom
    model provided by Watson Knowledge Studio, the public model for use with Knowledge
    Graph `en-news`, the default is`en-news`.
    """

    def __init__(self, model=None):
        """
        Initialize a NluEnrichmentRelations object.

        :param str model: (optional) *For use with `natural_language_understanding`
        enrichments only.* The enrichement model to use with relationship extraction. May
        be a custom model provided by Watson Knowledge Studio, the public model for use
        with Knowledge Graph `en-news`, the default is`en-news`.
        """
        self.model = model

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a NluEnrichmentRelations object from a json dictionary."""
        args = {}
        if 'model' in _dict:
            args['model'] = _dict.get('model')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'model') and self.model is not None:
            _dict['model'] = self.model
        return _dict

    def __str__(self):
        """Return a `str` version of this NluEnrichmentRelations object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class NluEnrichmentSemanticRoles(object):
    """
    An object specifiying the semantic roles enrichment and related parameters.

    :attr bool entities: (optional) When `true`, entities are extracted from the
    identified sentence parts.
    :attr bool keywords: (optional) When `true`, keywords are extracted from the
    identified sentence parts.
    :attr int limit: (optional) The maximum number of semantic roles enrichments to extact
    from each instance of the specified field.
    """

    def __init__(self, entities=None, keywords=None, limit=None):
        """
        Initialize a NluEnrichmentSemanticRoles object.

        :param bool entities: (optional) When `true`, entities are extracted from the
        identified sentence parts.
        :param bool keywords: (optional) When `true`, keywords are extracted from the
        identified sentence parts.
        :param int limit: (optional) The maximum number of semantic roles enrichments to
        extact from each instance of the specified field.
        """
        self.entities = entities
        self.keywords = keywords
        self.limit = limit

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a NluEnrichmentSemanticRoles object from a json dictionary."""
        args = {}
        if 'entities' in _dict:
            args['entities'] = _dict.get('entities')
        if 'keywords' in _dict:
            args['keywords'] = _dict.get('keywords')
        if 'limit' in _dict:
            args['limit'] = _dict.get('limit')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'entities') and self.entities is not None:
            _dict['entities'] = self.entities
        if hasattr(self, 'keywords') and self.keywords is not None:
            _dict['keywords'] = self.keywords
        if hasattr(self, 'limit') and self.limit is not None:
            _dict['limit'] = self.limit
        return _dict

    def __str__(self):
        """Return a `str` version of this NluEnrichmentSemanticRoles object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class NluEnrichmentSentiment(object):
    """
    An object specifying the sentiment extraction enrichment and related parameters.

    :attr bool document: (optional) When `true`, sentiment analysis is performed on the
    entire field.
    :attr list[str] targets: (optional) A comma-separated list of target strings that will
    have any associated sentiment analyzed.
    """

    def __init__(self, document=None, targets=None):
        """
        Initialize a NluEnrichmentSentiment object.

        :param bool document: (optional) When `true`, sentiment analysis is performed on
        the entire field.
        :param list[str] targets: (optional) A comma-separated list of target strings that
        will have any associated sentiment analyzed.
        """
        self.document = document
        self.targets = targets

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a NluEnrichmentSentiment object from a json dictionary."""
        args = {}
        if 'document' in _dict:
            args['document'] = _dict.get('document')
        if 'targets' in _dict:
            args['targets'] = _dict.get('targets')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'document') and self.document is not None:
            _dict['document'] = self.document
        if hasattr(self, 'targets') and self.targets is not None:
            _dict['targets'] = self.targets
        return _dict

    def __str__(self):
        """Return a `str` version of this NluEnrichmentSentiment object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class NormalizationOperation(object):
    """
    NormalizationOperation.

    :attr str operation: (optional) Identifies what type of operation to perform.
    **copy** - Copies the value of the **source_field** to the **destination_field**
    field. If the **destination_field** already exists, then the value of the
    **source_field** overwrites the original value of the **destination_field**.
    **move** - Renames (moves) the **source_field** to the **destination_field**. If the
    **destination_field** already exists, then the value of the **source_field**
    overwrites the original value of the **destination_field**. Rename is identical to
    copy, except that the **source_field** is removed after the value has been copied to
    the **destination_field** (it is the same as a _copy_ followed by a _remove_).
    **merge** - Merges the value of the **source_field** with the value of the
    **destination_field**. The **destination_field** is converted into an array if it is
    not already an array, and the value of the **source_field** is appended to the array.
    This operation removes the **source_field** after the merge. If the **source_field**
    does not exist in the current document, then the **destination_field** is still
    converted into an array (if it is not an array already). This conversion ensures the
    type for **destination_field** is consistent across all documents.
    **remove** - Deletes the **source_field** field. The **destination_field** is ignored
    for this operation.
    **remove_nulls** - Removes all nested null (blank) field values from the ingested
    document. **source_field** and **destination_field** are ignored by this operation
    because _remove_nulls_ operates on the entire ingested document. Typically,
    **remove_nulls** is invoked as the last normalization operation (if it is invoked at
    all, it can be time-expensive).
    :attr str source_field: (optional) The source field for the operation.
    :attr str destination_field: (optional) The destination field for the operation.
    """

    def __init__(self,
                 operation=None,
                 source_field=None,
                 destination_field=None):
        """
        Initialize a NormalizationOperation object.

        :param str operation: (optional) Identifies what type of operation to perform.
        **copy** - Copies the value of the **source_field** to the **destination_field**
        field. If the **destination_field** already exists, then the value of the
        **source_field** overwrites the original value of the **destination_field**.
        **move** - Renames (moves) the **source_field** to the **destination_field**. If
        the **destination_field** already exists, then the value of the **source_field**
        overwrites the original value of the **destination_field**. Rename is identical to
        copy, except that the **source_field** is removed after the value has been copied
        to the **destination_field** (it is the same as a _copy_ followed by a _remove_).
        **merge** - Merges the value of the **source_field** with the value of the
        **destination_field**. The **destination_field** is converted into an array if it
        is not already an array, and the value of the **source_field** is appended to the
        array. This operation removes the **source_field** after the merge. If the
        **source_field** does not exist in the current document, then the
        **destination_field** is still converted into an array (if it is not an array
        already). This conversion ensures the type for **destination_field** is consistent
        across all documents.
        **remove** - Deletes the **source_field** field. The **destination_field** is
        ignored for this operation.
        **remove_nulls** - Removes all nested null (blank) field values from the ingested
        document. **source_field** and **destination_field** are ignored by this operation
        because _remove_nulls_ operates on the entire ingested document. Typically,
        **remove_nulls** is invoked as the last normalization operation (if it is invoked
        at all, it can be time-expensive).
        :param str source_field: (optional) The source field for the operation.
        :param str destination_field: (optional) The destination field for the operation.
        """
        self.operation = operation
        self.source_field = source_field
        self.destination_field = destination_field

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a NormalizationOperation object from a json dictionary."""
        args = {}
        if 'operation' in _dict:
            args['operation'] = _dict.get('operation')
        if 'source_field' in _dict:
            args['source_field'] = _dict.get('source_field')
        if 'destination_field' in _dict:
            args['destination_field'] = _dict.get('destination_field')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'operation') and self.operation is not None:
            _dict['operation'] = self.operation
        if hasattr(self, 'source_field') and self.source_field is not None:
            _dict['source_field'] = self.source_field
        if hasattr(self,
                   'destination_field') and self.destination_field is not None:
            _dict['destination_field'] = self.destination_field
        return _dict

    def __str__(self):
        """Return a `str` version of this NormalizationOperation object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Notice(object):
    """
    A notice produced for the collection.

    :attr str notice_id: (optional) Identifies the notice. Many notices might have the
    same ID. This field exists so that user applications can programmatically identify a
    notice and take automatic corrective action. Typical notice IDs include:
    `index_failed`, `index_failed_too_many_requests`, `index_failed_incompatible_field`,
    `index_failed_cluster_unavailable`, `ingestion_timeout`, `ingestion_error`,
    `bad_request`, `internal_error`, `missing_model`, `unsupported_model`,
    `smart_document_understanding_failed_incompatible_field`,
    `smart_document_understanding_failed_internal_error`,
    `smart_document_understanding_failed_internal_error`,
    `smart_document_understanding_failed_warning`,
    `smart_document_understanding_page_error`,
    `smart_document_understanding_page_warning`. **Note:** This is not a complete list,
    other values might be returned.
    :attr datetime created: (optional) The creation date of the collection in the format
    yyyy-MM-dd'T'HH:mm:ss.SSS'Z'.
    :attr str document_id: (optional) Unique identifier of the document.
    :attr str query_id: (optional) Unique identifier of the query used for relevance
    training.
    :attr str severity: (optional) Severity level of the notice.
    :attr str step: (optional) Ingestion or training step in which the notice occurred.
    Typical step values include: `classify_elements`, `smartDocumentUnderstanding`,
    `ingestion`, `indexing`, `convert`. **Note:** This is not a complete list, other
    values might be returned.
    :attr str description: (optional) The description of the notice.
    """

    def __init__(self,
                 notice_id=None,
                 created=None,
                 document_id=None,
                 query_id=None,
                 severity=None,
                 step=None,
                 description=None):
        """
        Initialize a Notice object.

        :param str notice_id: (optional) Identifies the notice. Many notices might have
        the same ID. This field exists so that user applications can programmatically
        identify a notice and take automatic corrective action. Typical notice IDs
        include: `index_failed`, `index_failed_too_many_requests`,
        `index_failed_incompatible_field`, `index_failed_cluster_unavailable`,
        `ingestion_timeout`, `ingestion_error`, `bad_request`, `internal_error`,
        `missing_model`, `unsupported_model`,
        `smart_document_understanding_failed_incompatible_field`,
        `smart_document_understanding_failed_internal_error`,
        `smart_document_understanding_failed_internal_error`,
        `smart_document_understanding_failed_warning`,
        `smart_document_understanding_page_error`,
        `smart_document_understanding_page_warning`. **Note:** This is not a complete
        list, other values might be returned.
        :param datetime created: (optional) The creation date of the collection in the
        format yyyy-MM-dd'T'HH:mm:ss.SSS'Z'.
        :param str document_id: (optional) Unique identifier of the document.
        :param str query_id: (optional) Unique identifier of the query used for relevance
        training.
        :param str severity: (optional) Severity level of the notice.
        :param str step: (optional) Ingestion or training step in which the notice
        occurred. Typical step values include: `classify_elements`,
        `smartDocumentUnderstanding`, `ingestion`, `indexing`, `convert`. **Note:** This
        is not a complete list, other values might be returned.
        :param str description: (optional) The description of the notice.
        """
        self.notice_id = notice_id
        self.created = created
        self.document_id = document_id
        self.query_id = query_id
        self.severity = severity
        self.step = step
        self.description = description

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Notice object from a json dictionary."""
        args = {}
        if 'notice_id' in _dict:
            args['notice_id'] = _dict.get('notice_id')
        if 'created' in _dict:
            args['created'] = string_to_datetime(_dict.get('created'))
        if 'document_id' in _dict:
            args['document_id'] = _dict.get('document_id')
        if 'query_id' in _dict:
            args['query_id'] = _dict.get('query_id')
        if 'severity' in _dict:
            args['severity'] = _dict.get('severity')
        if 'step' in _dict:
            args['step'] = _dict.get('step')
        if 'description' in _dict:
            args['description'] = _dict.get('description')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'notice_id') and self.notice_id is not None:
            _dict['notice_id'] = self.notice_id
        if hasattr(self, 'created') and self.created is not None:
            _dict['created'] = datetime_to_string(self.created)
        if hasattr(self, 'document_id') and self.document_id is not None:
            _dict['document_id'] = self.document_id
        if hasattr(self, 'query_id') and self.query_id is not None:
            _dict['query_id'] = self.query_id
        if hasattr(self, 'severity') and self.severity is not None:
            _dict['severity'] = self.severity
        if hasattr(self, 'step') and self.step is not None:
            _dict['step'] = self.step
        if hasattr(self, 'description') and self.description is not None:
            _dict['description'] = self.description
        return _dict

    def __str__(self):
        """Return a `str` version of this Notice object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class PdfHeadingDetection(object):
    """
    PdfHeadingDetection.

    :attr list[FontSetting] fonts: (optional)
    """

    def __init__(self, fonts=None):
        """
        Initialize a PdfHeadingDetection object.

        :param list[FontSetting] fonts: (optional)
        """
        self.fonts = fonts

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a PdfHeadingDetection object from a json dictionary."""
        args = {}
        if 'fonts' in _dict:
            args['fonts'] = [
                FontSetting._from_dict(x) for x in (_dict.get('fonts'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'fonts') and self.fonts is not None:
            _dict['fonts'] = [x._to_dict() for x in self.fonts]
        return _dict

    def __str__(self):
        """Return a `str` version of this PdfHeadingDetection object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class PdfSettings(object):
    """
    A list of PDF conversion settings.

    :attr PdfHeadingDetection heading: (optional)
    """

    def __init__(self, heading=None):
        """
        Initialize a PdfSettings object.

        :param PdfHeadingDetection heading: (optional)
        """
        self.heading = heading

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a PdfSettings object from a json dictionary."""
        args = {}
        if 'heading' in _dict:
            args['heading'] = PdfHeadingDetection._from_dict(
                _dict.get('heading'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'heading') and self.heading is not None:
            _dict['heading'] = self.heading._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this PdfSettings object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryAggregation(object):
    """
    An aggregation produced by the Discovery service to analyze the input provided.

    :attr str type: (optional) The type of aggregation command used. For example: term,
    filter, max, min, etc.
    :attr list[AggregationResult] results: (optional) Array of aggregation results.
    :attr int matching_results: (optional) Number of matching results.
    :attr list[QueryAggregation] aggregations: (optional) Aggregations returned by the
    Discovery service.
    """

    def __init__(self,
                 type=None,
                 results=None,
                 matching_results=None,
                 aggregations=None):
        """
        Initialize a QueryAggregation object.

        :param str type: (optional) The type of aggregation command used. For example:
        term, filter, max, min, etc.
        :param list[AggregationResult] results: (optional) Array of aggregation results.
        :param int matching_results: (optional) Number of matching results.
        :param list[QueryAggregation] aggregations: (optional) Aggregations returned by
        the Discovery service.
        """
        self.type = type
        self.results = results
        self.matching_results = matching_results
        self.aggregations = aggregations

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryAggregation object from a json dictionary."""
        args = {}
        if 'type' in _dict:
            args['type'] = _dict.get('type')
        if 'results' in _dict:
            args['results'] = [
                AggregationResult._from_dict(x) for x in (_dict.get('results'))
            ]
        if 'matching_results' in _dict:
            args['matching_results'] = _dict.get('matching_results')
        if 'aggregations' in _dict:
            args['aggregations'] = [
                QueryAggregation._from_dict(x)
                for x in (_dict.get('aggregations'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'type') and self.type is not None:
            _dict['type'] = self.type
        if hasattr(self, 'results') and self.results is not None:
            _dict['results'] = [x._to_dict() for x in self.results]
        if hasattr(self,
                   'matching_results') and self.matching_results is not None:
            _dict['matching_results'] = self.matching_results
        if hasattr(self, 'aggregations') and self.aggregations is not None:
            _dict['aggregations'] = [x._to_dict() for x in self.aggregations]
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryAggregation object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryEntitiesContext(object):
    """
    Entity text to provide context for the queried entity and rank based on that
    association. For example, if you wanted to query the city of London in England your
    query would look for `London` with the context of `England`.

    :attr str text: (optional) Entity text to provide context for the queried entity and
    rank based on that association. For example, if you wanted to query the city of London
    in England your query would look for `London` with the context of `England`.
    """

    def __init__(self, text=None):
        """
        Initialize a QueryEntitiesContext object.

        :param str text: (optional) Entity text to provide context for the queried entity
        and rank based on that association. For example, if you wanted to query the city
        of London in England your query would look for `London` with the context of
        `England`.
        """
        self.text = text

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryEntitiesContext object from a json dictionary."""
        args = {}
        if 'text' in _dict:
            args['text'] = _dict.get('text')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'text') and self.text is not None:
            _dict['text'] = self.text
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryEntitiesContext object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryEntitiesEntity(object):
    """
    A text string that appears within the entity text field.

    :attr str text: (optional) Entity text content.
    :attr str type: (optional) The type of the specified entity.
    """

    def __init__(self, text=None, type=None):
        """
        Initialize a QueryEntitiesEntity object.

        :param str text: (optional) Entity text content.
        :param str type: (optional) The type of the specified entity.
        """
        self.text = text
        self.type = type

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryEntitiesEntity object from a json dictionary."""
        args = {}
        if 'text' in _dict:
            args['text'] = _dict.get('text')
        if 'type' in _dict:
            args['type'] = _dict.get('type')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'text') and self.text is not None:
            _dict['text'] = self.text
        if hasattr(self, 'type') and self.type is not None:
            _dict['type'] = self.type
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryEntitiesEntity object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryEntitiesResponse(object):
    """
    An object that contains an array of entities resulting from the query.

    :attr list[QueryEntitiesResponseItem] entities: (optional) Array of entities that
    results from the query.
    """

    def __init__(self, entities=None):
        """
        Initialize a QueryEntitiesResponse object.

        :param list[QueryEntitiesResponseItem] entities: (optional) Array of entities that
        results from the query.
        """
        self.entities = entities

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryEntitiesResponse object from a json dictionary."""
        args = {}
        if 'entities' in _dict:
            args['entities'] = [
                QueryEntitiesResponseItem._from_dict(x)
                for x in (_dict.get('entities'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'entities') and self.entities is not None:
            _dict['entities'] = [x._to_dict() for x in self.entities]
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryEntitiesResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryEntitiesResponseItem(object):
    """
    Object containing Entity query response information.

    :attr str text: (optional) Entity text content.
    :attr str type: (optional) The type of the result entity.
    :attr list[QueryEvidence] evidence: (optional) List of different evidentiary items to
    support the result.
    """

    def __init__(self, text=None, type=None, evidence=None):
        """
        Initialize a QueryEntitiesResponseItem object.

        :param str text: (optional) Entity text content.
        :param str type: (optional) The type of the result entity.
        :param list[QueryEvidence] evidence: (optional) List of different evidentiary
        items to support the result.
        """
        self.text = text
        self.type = type
        self.evidence = evidence

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryEntitiesResponseItem object from a json dictionary."""
        args = {}
        if 'text' in _dict:
            args['text'] = _dict.get('text')
        if 'type' in _dict:
            args['type'] = _dict.get('type')
        if 'evidence' in _dict:
            args['evidence'] = [
                QueryEvidence._from_dict(x) for x in (_dict.get('evidence'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'text') and self.text is not None:
            _dict['text'] = self.text
        if hasattr(self, 'type') and self.type is not None:
            _dict['type'] = self.type
        if hasattr(self, 'evidence') and self.evidence is not None:
            _dict['evidence'] = [x._to_dict() for x in self.evidence]
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryEntitiesResponseItem object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryEvidence(object):
    """
    Description of evidence location supporting Knoweldge Graph query result.

    :attr str document_id: (optional) The docuemnt ID (as indexed in Discovery) of the
    evidence location.
    :attr str field: (optional) The field of the document where the supporting evidence
    was identified.
    :attr int start_offset: (optional) The start location of the evidence in the
    identified field. This value is inclusive.
    :attr int end_offset: (optional) The end location of the evidence in the identified
    field. This value is inclusive.
    :attr list[QueryEvidenceEntity] entities: (optional) An array of entity objects that
    show evidence of the result.
    """

    def __init__(self,
                 document_id=None,
                 field=None,
                 start_offset=None,
                 end_offset=None,
                 entities=None):
        """
        Initialize a QueryEvidence object.

        :param str document_id: (optional) The docuemnt ID (as indexed in Discovery) of
        the evidence location.
        :param str field: (optional) The field of the document where the supporting
        evidence was identified.
        :param int start_offset: (optional) The start location of the evidence in the
        identified field. This value is inclusive.
        :param int end_offset: (optional) The end location of the evidence in the
        identified field. This value is inclusive.
        :param list[QueryEvidenceEntity] entities: (optional) An array of entity objects
        that show evidence of the result.
        """
        self.document_id = document_id
        self.field = field
        self.start_offset = start_offset
        self.end_offset = end_offset
        self.entities = entities

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryEvidence object from a json dictionary."""
        args = {}
        if 'document_id' in _dict:
            args['document_id'] = _dict.get('document_id')
        if 'field' in _dict:
            args['field'] = _dict.get('field')
        if 'start_offset' in _dict:
            args['start_offset'] = _dict.get('start_offset')
        if 'end_offset' in _dict:
            args['end_offset'] = _dict.get('end_offset')
        if 'entities' in _dict:
            args['entities'] = [
                QueryEvidenceEntity._from_dict(x)
                for x in (_dict.get('entities'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'document_id') and self.document_id is not None:
            _dict['document_id'] = self.document_id
        if hasattr(self, 'field') and self.field is not None:
            _dict['field'] = self.field
        if hasattr(self, 'start_offset') and self.start_offset is not None:
            _dict['start_offset'] = self.start_offset
        if hasattr(self, 'end_offset') and self.end_offset is not None:
            _dict['end_offset'] = self.end_offset
        if hasattr(self, 'entities') and self.entities is not None:
            _dict['entities'] = [x._to_dict() for x in self.entities]
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryEvidence object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryEvidenceEntity(object):
    """
    Entity description and location within evidence field.

    :attr str type: (optional) The entity type for this entity. Possible types vary based
    on model used.
    :attr str text: (optional) The original text of this entity as found in the evidence
    field.
    :attr int start_offset: (optional) The start location of the entity text in the
    identified field. This value is inclusive.
    :attr int end_offset: (optional) The end location of the entity text in the identified
    field. This value is exclusive.
    """

    def __init__(self, type=None, text=None, start_offset=None,
                 end_offset=None):
        """
        Initialize a QueryEvidenceEntity object.

        :param str type: (optional) The entity type for this entity. Possible types vary
        based on model used.
        :param str text: (optional) The original text of this entity as found in the
        evidence field.
        :param int start_offset: (optional) The start location of the entity text in the
        identified field. This value is inclusive.
        :param int end_offset: (optional) The end location of the entity text in the
        identified field. This value is exclusive.
        """
        self.type = type
        self.text = text
        self.start_offset = start_offset
        self.end_offset = end_offset

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryEvidenceEntity object from a json dictionary."""
        args = {}
        if 'type' in _dict:
            args['type'] = _dict.get('type')
        if 'text' in _dict:
            args['text'] = _dict.get('text')
        if 'start_offset' in _dict:
            args['start_offset'] = _dict.get('start_offset')
        if 'end_offset' in _dict:
            args['end_offset'] = _dict.get('end_offset')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'type') and self.type is not None:
            _dict['type'] = self.type
        if hasattr(self, 'text') and self.text is not None:
            _dict['text'] = self.text
        if hasattr(self, 'start_offset') and self.start_offset is not None:
            _dict['start_offset'] = self.start_offset
        if hasattr(self, 'end_offset') and self.end_offset is not None:
            _dict['end_offset'] = self.end_offset
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryEvidenceEntity object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryFilterType(object):
    """
    QueryFilterType.

    :attr list[str] exclude: (optional) A comma-separated list of types to exclude.
    :attr list[str] include: (optional) A comma-separated list of types to include. All
    other types are excluded.
    """

    def __init__(self, exclude=None, include=None):
        """
        Initialize a QueryFilterType object.

        :param list[str] exclude: (optional) A comma-separated list of types to exclude.
        :param list[str] include: (optional) A comma-separated list of types to include.
        All other types are excluded.
        """
        self.exclude = exclude
        self.include = include

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryFilterType object from a json dictionary."""
        args = {}
        if 'exclude' in _dict:
            args['exclude'] = _dict.get('exclude')
        if 'include' in _dict:
            args['include'] = _dict.get('include')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'exclude') and self.exclude is not None:
            _dict['exclude'] = self.exclude
        if hasattr(self, 'include') and self.include is not None:
            _dict['include'] = self.include
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryFilterType object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryNoticesResponse(object):
    """
    QueryNoticesResponse.

    :attr int matching_results: (optional) The number of matching results.
    :attr list[QueryNoticesResult] results: (optional) Array of document results that
    match the query.
    :attr list[QueryAggregation] aggregations: (optional) Array of aggregation results
    that match the query.
    :attr list[QueryPassages] passages: (optional) Array of passage results that match the
    query.
    :attr int duplicates_removed: (optional) The number of duplicates removed from this
    notices query.
    """

    def __init__(self,
                 matching_results=None,
                 results=None,
                 aggregations=None,
                 passages=None,
                 duplicates_removed=None):
        """
        Initialize a QueryNoticesResponse object.

        :param int matching_results: (optional) The number of matching results.
        :param list[QueryNoticesResult] results: (optional) Array of document results that
        match the query.
        :param list[QueryAggregation] aggregations: (optional) Array of aggregation
        results that match the query.
        :param list[QueryPassages] passages: (optional) Array of passage results that
        match the query.
        :param int duplicates_removed: (optional) The number of duplicates removed from
        this notices query.
        """
        self.matching_results = matching_results
        self.results = results
        self.aggregations = aggregations
        self.passages = passages
        self.duplicates_removed = duplicates_removed

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryNoticesResponse object from a json dictionary."""
        args = {}
        if 'matching_results' in _dict:
            args['matching_results'] = _dict.get('matching_results')
        if 'results' in _dict:
            args['results'] = [
                QueryNoticesResult._from_dict(x) for x in (_dict.get('results'))
            ]
        if 'aggregations' in _dict:
            args['aggregations'] = [
                QueryAggregation._from_dict(x)
                for x in (_dict.get('aggregations'))
            ]
        if 'passages' in _dict:
            args['passages'] = [
                QueryPassages._from_dict(x) for x in (_dict.get('passages'))
            ]
        if 'duplicates_removed' in _dict:
            args['duplicates_removed'] = _dict.get('duplicates_removed')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self,
                   'matching_results') and self.matching_results is not None:
            _dict['matching_results'] = self.matching_results
        if hasattr(self, 'results') and self.results is not None:
            _dict['results'] = [x._to_dict() for x in self.results]
        if hasattr(self, 'aggregations') and self.aggregations is not None:
            _dict['aggregations'] = [x._to_dict() for x in self.aggregations]
        if hasattr(self, 'passages') and self.passages is not None:
            _dict['passages'] = [x._to_dict() for x in self.passages]
        if hasattr(
                self,
                'duplicates_removed') and self.duplicates_removed is not None:
            _dict['duplicates_removed'] = self.duplicates_removed
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryNoticesResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryNoticesResult(object):
    """
    QueryNoticesResult.

    :attr str id: (optional) The unique identifier of the document.
    :attr dict metadata: (optional) Metadata of the document.
    :attr str collection_id: (optional) The collection ID of the collection containing the
    document for this result.
    :attr QueryResultMetadata result_metadata: (optional) Metadata of a query result.
    :attr str title: (optional) Automatically extracted result title.
    :attr int code: (optional) The internal status code returned by the ingestion
    subsystem indicating the overall result of ingesting the source document.
    :attr str filename: (optional) Name of the original source file (if available).
    :attr str file_type: (optional) The type of the original source file.
    :attr str sha1: (optional) The SHA-1 hash of the original source file (formatted as a
    hexadecimal string).
    :attr list[Notice] notices: (optional) Array of notices for the document.
    """

    def __init__(self,
                 id=None,
                 metadata=None,
                 collection_id=None,
                 result_metadata=None,
                 title=None,
                 code=None,
                 filename=None,
                 file_type=None,
                 sha1=None,
                 notices=None,
                 **kwargs):
        """
        Initialize a QueryNoticesResult object.

        :param str id: (optional) The unique identifier of the document.
        :param dict metadata: (optional) Metadata of the document.
        :param str collection_id: (optional) The collection ID of the collection
        containing the document for this result.
        :param QueryResultMetadata result_metadata: (optional) Metadata of a query result.
        :param str title: (optional) Automatically extracted result title.
        :param int code: (optional) The internal status code returned by the ingestion
        subsystem indicating the overall result of ingesting the source document.
        :param str filename: (optional) Name of the original source file (if available).
        :param str file_type: (optional) The type of the original source file.
        :param str sha1: (optional) The SHA-1 hash of the original source file (formatted
        as a hexadecimal string).
        :param list[Notice] notices: (optional) Array of notices for the document.
        :param **kwargs: (optional) Any additional properties.
        """
        self.id = id
        self.metadata = metadata
        self.collection_id = collection_id
        self.result_metadata = result_metadata
        self.title = title
        self.code = code
        self.filename = filename
        self.file_type = file_type
        self.sha1 = sha1
        self.notices = notices
        for _key, _value in kwargs.items():
            setattr(self, _key, _value)

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryNoticesResult object from a json dictionary."""
        args = {}
        xtra = _dict.copy()
        if 'id' in _dict:
            args['id'] = _dict.get('id')
            del xtra['id']
        if 'metadata' in _dict:
            args['metadata'] = _dict.get('metadata')
            del xtra['metadata']
        if 'collection_id' in _dict:
            args['collection_id'] = _dict.get('collection_id')
            del xtra['collection_id']
        if 'result_metadata' in _dict:
            args['result_metadata'] = QueryResultMetadata._from_dict(
                _dict.get('result_metadata'))
            del xtra['result_metadata']
        if 'title' in _dict:
            args['title'] = _dict.get('title')
            del xtra['title']
        if 'code' in _dict:
            args['code'] = _dict.get('code')
            del xtra['code']
        if 'filename' in _dict:
            args['filename'] = _dict.get('filename')
            del xtra['filename']
        if 'file_type' in _dict:
            args['file_type'] = _dict.get('file_type')
            del xtra['file_type']
        if 'sha1' in _dict:
            args['sha1'] = _dict.get('sha1')
            del xtra['sha1']
        if 'notices' in _dict:
            args['notices'] = [
                Notice._from_dict(x) for x in (_dict.get('notices'))
            ]
            del xtra['notices']
        args.update(xtra)
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'id') and self.id is not None:
            _dict['id'] = self.id
        if hasattr(self, 'metadata') and self.metadata is not None:
            _dict['metadata'] = self.metadata
        if hasattr(self, 'collection_id') and self.collection_id is not None:
            _dict['collection_id'] = self.collection_id
        if hasattr(self,
                   'result_metadata') and self.result_metadata is not None:
            _dict['result_metadata'] = self.result_metadata._to_dict()
        if hasattr(self, 'title') and self.title is not None:
            _dict['title'] = self.title
        if hasattr(self, 'code') and self.code is not None:
            _dict['code'] = self.code
        if hasattr(self, 'filename') and self.filename is not None:
            _dict['filename'] = self.filename
        if hasattr(self, 'file_type') and self.file_type is not None:
            _dict['file_type'] = self.file_type
        if hasattr(self, 'sha1') and self.sha1 is not None:
            _dict['sha1'] = self.sha1
        if hasattr(self, 'notices') and self.notices is not None:
            _dict['notices'] = [x._to_dict() for x in self.notices]
        if hasattr(self, '_additionalProperties'):
            for _key in self._additionalProperties:
                _value = getattr(self, _key, None)
                if _value is not None:
                    _dict[_key] = _value
        return _dict

    def __setattr__(self, name, value):
        properties = {
            'id', 'metadata', 'collection_id', 'result_metadata', 'title',
            'code', 'filename', 'file_type', 'sha1', 'notices'
        }
        if not hasattr(self, '_additionalProperties'):
            super(QueryNoticesResult, self).__setattr__('_additionalProperties',
                                                        set())
        if name not in properties:
            self._additionalProperties.add(name)
        super(QueryNoticesResult, self).__setattr__(name, value)

    def __str__(self):
        """Return a `str` version of this QueryNoticesResult object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryPassages(object):
    """
    QueryPassages.

    :attr str document_id: (optional) The unique identifier of the document from which the
    passage has been extracted.
    :attr float passage_score: (optional) The confidence score of the passages's analysis.
    A higher score indicates greater confidence.
    :attr str passage_text: (optional) The content of the extracted passage.
    :attr int start_offset: (optional) The position of the first character of the
    extracted passage in the originating field.
    :attr int end_offset: (optional) The position of the last character of the extracted
    passage in the originating field.
    :attr str field: (optional) The label of the field from which the passage has been
    extracted.
    """

    def __init__(self,
                 document_id=None,
                 passage_score=None,
                 passage_text=None,
                 start_offset=None,
                 end_offset=None,
                 field=None):
        """
        Initialize a QueryPassages object.

        :param str document_id: (optional) The unique identifier of the document from
        which the passage has been extracted.
        :param float passage_score: (optional) The confidence score of the passages's
        analysis. A higher score indicates greater confidence.
        :param str passage_text: (optional) The content of the extracted passage.
        :param int start_offset: (optional) The position of the first character of the
        extracted passage in the originating field.
        :param int end_offset: (optional) The position of the last character of the
        extracted passage in the originating field.
        :param str field: (optional) The label of the field from which the passage has
        been extracted.
        """
        self.document_id = document_id
        self.passage_score = passage_score
        self.passage_text = passage_text
        self.start_offset = start_offset
        self.end_offset = end_offset
        self.field = field

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryPassages object from a json dictionary."""
        args = {}
        if 'document_id' in _dict:
            args['document_id'] = _dict.get('document_id')
        if 'passage_score' in _dict:
            args['passage_score'] = _dict.get('passage_score')
        if 'passage_text' in _dict:
            args['passage_text'] = _dict.get('passage_text')
        if 'start_offset' in _dict:
            args['start_offset'] = _dict.get('start_offset')
        if 'end_offset' in _dict:
            args['end_offset'] = _dict.get('end_offset')
        if 'field' in _dict:
            args['field'] = _dict.get('field')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'document_id') and self.document_id is not None:
            _dict['document_id'] = self.document_id
        if hasattr(self, 'passage_score') and self.passage_score is not None:
            _dict['passage_score'] = self.passage_score
        if hasattr(self, 'passage_text') and self.passage_text is not None:
            _dict['passage_text'] = self.passage_text
        if hasattr(self, 'start_offset') and self.start_offset is not None:
            _dict['start_offset'] = self.start_offset
        if hasattr(self, 'end_offset') and self.end_offset is not None:
            _dict['end_offset'] = self.end_offset
        if hasattr(self, 'field') and self.field is not None:
            _dict['field'] = self.field
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryPassages object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryRelationsArgument(object):
    """
    QueryRelationsArgument.

    :attr list[QueryEntitiesEntity] entities: (optional) Array of query entities.
    """

    def __init__(self, entities=None):
        """
        Initialize a QueryRelationsArgument object.

        :param list[QueryEntitiesEntity] entities: (optional) Array of query entities.
        """
        self.entities = entities

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryRelationsArgument object from a json dictionary."""
        args = {}
        if 'entities' in _dict:
            args['entities'] = [
                QueryEntitiesEntity._from_dict(x)
                for x in (_dict.get('entities'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'entities') and self.entities is not None:
            _dict['entities'] = [x._to_dict() for x in self.entities]
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryRelationsArgument object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryRelationsEntity(object):
    """
    QueryRelationsEntity.

    :attr str text: (optional) Entity text content.
    :attr str type: (optional) The type of the specified entity.
    :attr bool exact: (optional) If false, implicit querying is performed. The default is
    `false`.
    """

    def __init__(self, text=None, type=None, exact=None):
        """
        Initialize a QueryRelationsEntity object.

        :param str text: (optional) Entity text content.
        :param str type: (optional) The type of the specified entity.
        :param bool exact: (optional) If false, implicit querying is performed. The
        default is `false`.
        """
        self.text = text
        self.type = type
        self.exact = exact

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryRelationsEntity object from a json dictionary."""
        args = {}
        if 'text' in _dict:
            args['text'] = _dict.get('text')
        if 'type' in _dict:
            args['type'] = _dict.get('type')
        if 'exact' in _dict:
            args['exact'] = _dict.get('exact')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'text') and self.text is not None:
            _dict['text'] = self.text
        if hasattr(self, 'type') and self.type is not None:
            _dict['type'] = self.type
        if hasattr(self, 'exact') and self.exact is not None:
            _dict['exact'] = self.exact
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryRelationsEntity object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryRelationsFilter(object):
    """
    QueryRelationsFilter.

    :attr QueryFilterType relation_types: (optional)
    :attr QueryFilterType entity_types: (optional)
    :attr list[str] document_ids: (optional) A comma-separated list of document IDs to
    include in the query.
    """

    def __init__(self,
                 relation_types=None,
                 entity_types=None,
                 document_ids=None):
        """
        Initialize a QueryRelationsFilter object.

        :param QueryFilterType relation_types: (optional)
        :param QueryFilterType entity_types: (optional)
        :param list[str] document_ids: (optional) A comma-separated list of document IDs
        to include in the query.
        """
        self.relation_types = relation_types
        self.entity_types = entity_types
        self.document_ids = document_ids

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryRelationsFilter object from a json dictionary."""
        args = {}
        if 'relation_types' in _dict:
            args['relation_types'] = QueryFilterType._from_dict(
                _dict.get('relation_types'))
        if 'entity_types' in _dict:
            args['entity_types'] = QueryFilterType._from_dict(
                _dict.get('entity_types'))
        if 'document_ids' in _dict:
            args['document_ids'] = _dict.get('document_ids')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'relation_types') and self.relation_types is not None:
            _dict['relation_types'] = self.relation_types._to_dict()
        if hasattr(self, 'entity_types') and self.entity_types is not None:
            _dict['entity_types'] = self.entity_types._to_dict()
        if hasattr(self, 'document_ids') and self.document_ids is not None:
            _dict['document_ids'] = self.document_ids
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryRelationsFilter object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryRelationsRelationship(object):
    """
    QueryRelationsRelationship.

    :attr str type: (optional) The identified relationship type.
    :attr int frequency: (optional) The number of times the relationship is mentioned.
    :attr list[QueryRelationsArgument] arguments: (optional) Information about the
    relationship.
    :attr list[QueryEvidence] evidence: (optional) List of different evidentiary items to
    support the result.
    """

    def __init__(self, type=None, frequency=None, arguments=None,
                 evidence=None):
        """
        Initialize a QueryRelationsRelationship object.

        :param str type: (optional) The identified relationship type.
        :param int frequency: (optional) The number of times the relationship is
        mentioned.
        :param list[QueryRelationsArgument] arguments: (optional) Information about the
        relationship.
        :param list[QueryEvidence] evidence: (optional) List of different evidentiary
        items to support the result.
        """
        self.type = type
        self.frequency = frequency
        self.arguments = arguments
        self.evidence = evidence

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryRelationsRelationship object from a json dictionary."""
        args = {}
        if 'type' in _dict:
            args['type'] = _dict.get('type')
        if 'frequency' in _dict:
            args['frequency'] = _dict.get('frequency')
        if 'arguments' in _dict:
            args['arguments'] = [
                QueryRelationsArgument._from_dict(x)
                for x in (_dict.get('arguments'))
            ]
        if 'evidence' in _dict:
            args['evidence'] = [
                QueryEvidence._from_dict(x) for x in (_dict.get('evidence'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'type') and self.type is not None:
            _dict['type'] = self.type
        if hasattr(self, 'frequency') and self.frequency is not None:
            _dict['frequency'] = self.frequency
        if hasattr(self, 'arguments') and self.arguments is not None:
            _dict['arguments'] = [x._to_dict() for x in self.arguments]
        if hasattr(self, 'evidence') and self.evidence is not None:
            _dict['evidence'] = [x._to_dict() for x in self.evidence]
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryRelationsRelationship object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryRelationsResponse(object):
    """
    QueryRelationsResponse.

    :attr list[QueryRelationsRelationship] relations: (optional) Array of relationships
    for the relations query.
    """

    def __init__(self, relations=None):
        """
        Initialize a QueryRelationsResponse object.

        :param list[QueryRelationsRelationship] relations: (optional) Array of
        relationships for the relations query.
        """
        self.relations = relations

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryRelationsResponse object from a json dictionary."""
        args = {}
        if 'relations' in _dict:
            args['relations'] = [
                QueryRelationsRelationship._from_dict(x)
                for x in (_dict.get('relations'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'relations') and self.relations is not None:
            _dict['relations'] = [x._to_dict() for x in self.relations]
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryRelationsResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryResponse(object):
    """
    A response containing the documents and aggregations for the query.

    :attr int matching_results: (optional) The number of matching results for the query.
    :attr list[QueryResult] results: (optional) Array of document results for the query.
    :attr list[QueryAggregation] aggregations: (optional) Array of aggregation results for
    the query.
    :attr list[QueryPassages] passages: (optional) Array of passage results for the query.
    :attr int duplicates_removed: (optional) The number of duplicate results removed.
    :attr str session_token: (optional) The session token for this query. The session
    token can be used to add events associated with this query to the query and event log.
    **Important:** Session tokens are case sensitive.
    :attr RetrievalDetails retrieval_details: (optional) An object contain retrieval type
    information.
    """

    def __init__(self,
                 matching_results=None,
                 results=None,
                 aggregations=None,
                 passages=None,
                 duplicates_removed=None,
                 session_token=None,
                 retrieval_details=None):
        """
        Initialize a QueryResponse object.

        :param int matching_results: (optional) The number of matching results for the
        query.
        :param list[QueryResult] results: (optional) Array of document results for the
        query.
        :param list[QueryAggregation] aggregations: (optional) Array of aggregation
        results for the query.
        :param list[QueryPassages] passages: (optional) Array of passage results for the
        query.
        :param int duplicates_removed: (optional) The number of duplicate results removed.
        :param str session_token: (optional) The session token for this query. The session
        token can be used to add events associated with this query to the query and event
        log.
        **Important:** Session tokens are case sensitive.
        :param RetrievalDetails retrieval_details: (optional) An object contain retrieval
        type information.
        """
        self.matching_results = matching_results
        self.results = results
        self.aggregations = aggregations
        self.passages = passages
        self.duplicates_removed = duplicates_removed
        self.session_token = session_token
        self.retrieval_details = retrieval_details

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryResponse object from a json dictionary."""
        args = {}
        if 'matching_results' in _dict:
            args['matching_results'] = _dict.get('matching_results')
        if 'results' in _dict:
            args['results'] = [
                QueryResult._from_dict(x) for x in (_dict.get('results'))
            ]
        if 'aggregations' in _dict:
            args['aggregations'] = [
                QueryAggregation._from_dict(x)
                for x in (_dict.get('aggregations'))
            ]
        if 'passages' in _dict:
            args['passages'] = [
                QueryPassages._from_dict(x) for x in (_dict.get('passages'))
            ]
        if 'duplicates_removed' in _dict:
            args['duplicates_removed'] = _dict.get('duplicates_removed')
        if 'session_token' in _dict:
            args['session_token'] = _dict.get('session_token')
        if 'retrieval_details' in _dict:
            args['retrieval_details'] = RetrievalDetails._from_dict(
                _dict.get('retrieval_details'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self,
                   'matching_results') and self.matching_results is not None:
            _dict['matching_results'] = self.matching_results
        if hasattr(self, 'results') and self.results is not None:
            _dict['results'] = [x._to_dict() for x in self.results]
        if hasattr(self, 'aggregations') and self.aggregations is not None:
            _dict['aggregations'] = [x._to_dict() for x in self.aggregations]
        if hasattr(self, 'passages') and self.passages is not None:
            _dict['passages'] = [x._to_dict() for x in self.passages]
        if hasattr(
                self,
                'duplicates_removed') and self.duplicates_removed is not None:
            _dict['duplicates_removed'] = self.duplicates_removed
        if hasattr(self, 'session_token') and self.session_token is not None:
            _dict['session_token'] = self.session_token
        if hasattr(self,
                   'retrieval_details') and self.retrieval_details is not None:
            _dict['retrieval_details'] = self.retrieval_details._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryResult(object):
    """
    QueryResult.

    :attr str id: (optional) The unique identifier of the document.
    :attr dict metadata: (optional) Metadata of the document.
    :attr str collection_id: (optional) The collection ID of the collection containing the
    document for this result.
    :attr QueryResultMetadata result_metadata: (optional) Metadata of a query result.
    :attr str title: (optional) Automatically extracted result title.
    """

    def __init__(self,
                 id=None,
                 metadata=None,
                 collection_id=None,
                 result_metadata=None,
                 title=None,
                 **kwargs):
        """
        Initialize a QueryResult object.

        :param str id: (optional) The unique identifier of the document.
        :param dict metadata: (optional) Metadata of the document.
        :param str collection_id: (optional) The collection ID of the collection
        containing the document for this result.
        :param QueryResultMetadata result_metadata: (optional) Metadata of a query result.
        :param str title: (optional) Automatically extracted result title.
        :param **kwargs: (optional) Any additional properties.
        """
        self.id = id
        self.metadata = metadata
        self.collection_id = collection_id
        self.result_metadata = result_metadata
        self.title = title
        for _key, _value in kwargs.items():
            setattr(self, _key, _value)

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryResult object from a json dictionary."""
        args = {}
        xtra = _dict.copy()
        if 'id' in _dict:
            args['id'] = _dict.get('id')
            del xtra['id']
        if 'metadata' in _dict:
            args['metadata'] = _dict.get('metadata')
            del xtra['metadata']
        if 'collection_id' in _dict:
            args['collection_id'] = _dict.get('collection_id')
            del xtra['collection_id']
        if 'result_metadata' in _dict:
            args['result_metadata'] = QueryResultMetadata._from_dict(
                _dict.get('result_metadata'))
            del xtra['result_metadata']
        if 'title' in _dict:
            args['title'] = _dict.get('title')
            del xtra['title']
        args.update(xtra)
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'id') and self.id is not None:
            _dict['id'] = self.id
        if hasattr(self, 'metadata') and self.metadata is not None:
            _dict['metadata'] = self.metadata
        if hasattr(self, 'collection_id') and self.collection_id is not None:
            _dict['collection_id'] = self.collection_id
        if hasattr(self,
                   'result_metadata') and self.result_metadata is not None:
            _dict['result_metadata'] = self.result_metadata._to_dict()
        if hasattr(self, 'title') and self.title is not None:
            _dict['title'] = self.title
        if hasattr(self, '_additionalProperties'):
            for _key in self._additionalProperties:
                _value = getattr(self, _key, None)
                if _value is not None:
                    _dict[_key] = _value
        return _dict

    def __setattr__(self, name, value):
        properties = {
            'id', 'metadata', 'collection_id', 'result_metadata', 'title'
        }
        if not hasattr(self, '_additionalProperties'):
            super(QueryResult, self).__setattr__('_additionalProperties', set())
        if name not in properties:
            self._additionalProperties.add(name)
        super(QueryResult, self).__setattr__(name, value)

    def __str__(self):
        """Return a `str` version of this QueryResult object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class QueryResultMetadata(object):
    """
    Metadata of a query result.

    :attr float score: An unbounded measure of the relevance of a particular result,
    dependent on the query and matching document. A higher score indicates a greater match
    to the query parameters.
    :attr float confidence: (optional) The confidence score for the given result.
    Calculated based on how relevant the result is estimated to be. confidence can range
    from `0.0` to `1.0`. The higher the number, the more relevant the document. The
    `confidence` value for a result was calculated using the model specified in the
    `document_retrieval_strategy` field of the result set.
    """

    def __init__(self, score, confidence=None):
        """
        Initialize a QueryResultMetadata object.

        :param float score: An unbounded measure of the relevance of a particular result,
        dependent on the query and matching document. A higher score indicates a greater
        match to the query parameters.
        :param float confidence: (optional) The confidence score for the given result.
        Calculated based on how relevant the result is estimated to be. confidence can
        range from `0.0` to `1.0`. The higher the number, the more relevant the document.
        The `confidence` value for a result was calculated using the model specified in
        the `document_retrieval_strategy` field of the result set.
        """
        self.score = score
        self.confidence = confidence

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a QueryResultMetadata object from a json dictionary."""
        args = {}
        if 'score' in _dict:
            args['score'] = _dict.get('score')
        else:
            raise ValueError(
                'Required property \'score\' not present in QueryResultMetadata JSON'
            )
        if 'confidence' in _dict:
            args['confidence'] = _dict.get('confidence')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'score') and self.score is not None:
            _dict['score'] = self.score
        if hasattr(self, 'confidence') and self.confidence is not None:
            _dict['confidence'] = self.confidence
        return _dict

    def __str__(self):
        """Return a `str` version of this QueryResultMetadata object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class RetrievalDetails(object):
    """
    An object contain retrieval type information.

    :attr str document_retrieval_strategy: (optional) Indentifies the document retrieval
    strategy used for this query. `relevancy_training` indicates that the results were
    returned using a relevancy trained model. `continuous_relevancy_training` indicates
    that the results were returned using the continuous relevancy training model created
    by result feedback analysis. `untrained` means the results were returned using the
    standard untrained model.
     **Note**: In the event of trained collections being queried, but the trained model is
    not used to return results, the **document_retrieval_strategy** will be listed as
    `untrained`.
    """

    def __init__(self, document_retrieval_strategy=None):
        """
        Initialize a RetrievalDetails object.

        :param str document_retrieval_strategy: (optional) Indentifies the document
        retrieval strategy used for this query. `relevancy_training` indicates that the
        results were returned using a relevancy trained model.
        `continuous_relevancy_training` indicates that the results were returned using the
        continuous relevancy training model created by result feedback analysis.
        `untrained` means the results were returned using the standard untrained model.
         **Note**: In the event of trained collections being queried, but the trained
        model is not used to return results, the **document_retrieval_strategy** will be
        listed as `untrained`.
        """
        self.document_retrieval_strategy = document_retrieval_strategy

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a RetrievalDetails object from a json dictionary."""
        args = {}
        if 'document_retrieval_strategy' in _dict:
            args['document_retrieval_strategy'] = _dict.get(
                'document_retrieval_strategy')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'document_retrieval_strategy'
                  ) and self.document_retrieval_strategy is not None:
            _dict[
                'document_retrieval_strategy'] = self.document_retrieval_strategy
        return _dict

    def __str__(self):
        """Return a `str` version of this RetrievalDetails object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SearchStatus(object):
    """
    Information about the Continuous Relevancy Training for this environment.

    :attr str scope: (optional) Current scope of the training. Always returned as
    `environment`.
    :attr str status: (optional) The current status of Continuous Relevancy Training for
    this environment.
    :attr str status_description: (optional) Long description of the current Continuous
    Relevancy Training status.
    :attr date last_trained: (optional) The date stamp of the most recent completed
    training for this environment.
    """

    def __init__(self,
                 scope=None,
                 status=None,
                 status_description=None,
                 last_trained=None):
        """
        Initialize a SearchStatus object.

        :param str scope: (optional) Current scope of the training. Always returned as
        `environment`.
        :param str status: (optional) The current status of Continuous Relevancy Training
        for this environment.
        :param str status_description: (optional) Long description of the current
        Continuous Relevancy Training status.
        :param date last_trained: (optional) The date stamp of the most recent completed
        training for this environment.
        """
        self.scope = scope
        self.status = status
        self.status_description = status_description
        self.last_trained = last_trained

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SearchStatus object from a json dictionary."""
        args = {}
        if 'scope' in _dict:
            args['scope'] = _dict.get('scope')
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        if 'status_description' in _dict:
            args['status_description'] = _dict.get('status_description')
        if 'last_trained' in _dict:
            args['last_trained'] = _dict.get('last_trained')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'scope') and self.scope is not None:
            _dict['scope'] = self.scope
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        if hasattr(
                self,
                'status_description') and self.status_description is not None:
            _dict['status_description'] = self.status_description
        if hasattr(self, 'last_trained') and self.last_trained is not None:
            _dict['last_trained'] = self.last_trained
        return _dict

    def __str__(self):
        """Return a `str` version of this SearchStatus object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SegmentSettings(object):
    """
    A list of Document Segmentation settings.

    :attr bool enabled: (optional) Enables/disables the Document Segmentation feature.
    :attr list[str] selector_tags: (optional) Defines the heading level that splits into
    document segments. Valid values are h1, h2, h3, h4, h5, h6. The content of the header
    field that the segmentation splits at is used as the **title** field for that
    segmented result.
    """

    def __init__(self, enabled=None, selector_tags=None):
        """
        Initialize a SegmentSettings object.

        :param bool enabled: (optional) Enables/disables the Document Segmentation
        feature.
        :param list[str] selector_tags: (optional) Defines the heading level that splits
        into document segments. Valid values are h1, h2, h3, h4, h5, h6. The content of
        the header field that the segmentation splits at is used as the **title** field
        for that segmented result.
        """
        self.enabled = enabled
        self.selector_tags = selector_tags

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SegmentSettings object from a json dictionary."""
        args = {}
        if 'enabled' in _dict:
            args['enabled'] = _dict.get('enabled')
        if 'selector_tags' in _dict:
            args['selector_tags'] = _dict.get('selector_tags')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'enabled') and self.enabled is not None:
            _dict['enabled'] = self.enabled
        if hasattr(self, 'selector_tags') and self.selector_tags is not None:
            _dict['selector_tags'] = self.selector_tags
        return _dict

    def __str__(self):
        """Return a `str` version of this SegmentSettings object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Source(object):
    """
    Object containing source parameters for the configuration.

    :attr str type: (optional) The type of source to connect to.
    -  `box` indicates the configuration is to connect an instance of Enterprise Box.
    -  `salesforce` indicates the configuration is to connect to Salesforce.
    -  `sharepoint` indicates the configuration is to connect to Microsoft SharePoint
    Online.
    -  `web_crawl` indicates the configuration is to perform a web page crawl.
    -  `cloud_object_storage` indicates the configuration is to connect to a cloud object
    store.
    :attr str credential_id: (optional) The **credential_id** of the credentials to use to
    connect to the source. Credentials are defined using the **credentials** method. The
    **source_type** of the credentials used must match the **type** field specified in
    this object.
    :attr SourceSchedule schedule: (optional) Object containing the schedule information
    for the source.
    :attr SourceOptions options: (optional) The **options** object defines which items to
    crawl from the source system.
    """

    def __init__(self,
                 type=None,
                 credential_id=None,
                 schedule=None,
                 options=None):
        """
        Initialize a Source object.

        :param str type: (optional) The type of source to connect to.
        -  `box` indicates the configuration is to connect an instance of Enterprise Box.
        -  `salesforce` indicates the configuration is to connect to Salesforce.
        -  `sharepoint` indicates the configuration is to connect to Microsoft SharePoint
        Online.
        -  `web_crawl` indicates the configuration is to perform a web page crawl.
        -  `cloud_object_storage` indicates the configuration is to connect to a cloud
        object store.
        :param str credential_id: (optional) The **credential_id** of the credentials to
        use to connect to the source. Credentials are defined using the **credentials**
        method. The **source_type** of the credentials used must match the **type** field
        specified in this object.
        :param SourceSchedule schedule: (optional) Object containing the schedule
        information for the source.
        :param SourceOptions options: (optional) The **options** object defines which
        items to crawl from the source system.
        """
        self.type = type
        self.credential_id = credential_id
        self.schedule = schedule
        self.options = options

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Source object from a json dictionary."""
        args = {}
        if 'type' in _dict:
            args['type'] = _dict.get('type')
        if 'credential_id' in _dict:
            args['credential_id'] = _dict.get('credential_id')
        if 'schedule' in _dict:
            args['schedule'] = SourceSchedule._from_dict(_dict.get('schedule'))
        if 'options' in _dict:
            args['options'] = SourceOptions._from_dict(_dict.get('options'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'type') and self.type is not None:
            _dict['type'] = self.type
        if hasattr(self, 'credential_id') and self.credential_id is not None:
            _dict['credential_id'] = self.credential_id
        if hasattr(self, 'schedule') and self.schedule is not None:
            _dict['schedule'] = self.schedule._to_dict()
        if hasattr(self, 'options') and self.options is not None:
            _dict['options'] = self.options._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this Source object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SourceOptions(object):
    """
    The **options** object defines which items to crawl from the source system.

    :attr list[SourceOptionsFolder] folders: (optional) Array of folders to crawl from the
    Box source. Only valid, and required, when the **type** field of the **source** object
    is set to `box`.
    :attr list[SourceOptionsObject] objects: (optional) Array of Salesforce document
    object types to crawl from the Salesforce source. Only valid, and required, when the
    **type** field of the **source** object is set to `salesforce`.
    :attr list[SourceOptionsSiteColl] site_collections: (optional) Array of Microsoft
    SharePointoint Online site collections to crawl from the SharePoint source. Only valid
    and required when the **type** field of the **source** object is set to `sharepoint`.
    :attr list[SourceOptionsWebCrawl] urls: (optional) Array of Web page URLs to begin
    crawling the web from. Only valid and required when the **type** field of the
    **source** object is set to `web_crawl`.
    :attr list[SourceOptionsBuckets] buckets: (optional) Array of cloud object store
    buckets to begin crawling. Only valid and required when the **type** field of the
    **source** object is set to `cloud_object_store`, and the **crawl_all_buckets** field
    is `false` or not specified.
    :attr bool crawl_all_buckets: (optional) When `true`, all buckets in the specified
    cloud object store are crawled. If set to `true`, the **buckets** array must not be
    specified.
    """

    def __init__(self,
                 folders=None,
                 objects=None,
                 site_collections=None,
                 urls=None,
                 buckets=None,
                 crawl_all_buckets=None):
        """
        Initialize a SourceOptions object.

        :param list[SourceOptionsFolder] folders: (optional) Array of folders to crawl
        from the Box source. Only valid, and required, when the **type** field of the
        **source** object is set to `box`.
        :param list[SourceOptionsObject] objects: (optional) Array of Salesforce document
        object types to crawl from the Salesforce source. Only valid, and required, when
        the **type** field of the **source** object is set to `salesforce`.
        :param list[SourceOptionsSiteColl] site_collections: (optional) Array of Microsoft
        SharePointoint Online site collections to crawl from the SharePoint source. Only
        valid and required when the **type** field of the **source** object is set to
        `sharepoint`.
        :param list[SourceOptionsWebCrawl] urls: (optional) Array of Web page URLs to
        begin crawling the web from. Only valid and required when the **type** field of
        the **source** object is set to `web_crawl`.
        :param list[SourceOptionsBuckets] buckets: (optional) Array of cloud object store
        buckets to begin crawling. Only valid and required when the **type** field of the
        **source** object is set to `cloud_object_store`, and the **crawl_all_buckets**
        field is `false` or not specified.
        :param bool crawl_all_buckets: (optional) When `true`, all buckets in the
        specified cloud object store are crawled. If set to `true`, the **buckets** array
        must not be specified.
        """
        self.folders = folders
        self.objects = objects
        self.site_collections = site_collections
        self.urls = urls
        self.buckets = buckets
        self.crawl_all_buckets = crawl_all_buckets

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SourceOptions object from a json dictionary."""
        args = {}
        if 'folders' in _dict:
            args['folders'] = [
                SourceOptionsFolder._from_dict(x)
                for x in (_dict.get('folders'))
            ]
        if 'objects' in _dict:
            args['objects'] = [
                SourceOptionsObject._from_dict(x)
                for x in (_dict.get('objects'))
            ]
        if 'site_collections' in _dict:
            args['site_collections'] = [
                SourceOptionsSiteColl._from_dict(x)
                for x in (_dict.get('site_collections'))
            ]
        if 'urls' in _dict:
            args['urls'] = [
                SourceOptionsWebCrawl._from_dict(x) for x in (_dict.get('urls'))
            ]
        if 'buckets' in _dict:
            args['buckets'] = [
                SourceOptionsBuckets._from_dict(x)
                for x in (_dict.get('buckets'))
            ]
        if 'crawl_all_buckets' in _dict:
            args['crawl_all_buckets'] = _dict.get('crawl_all_buckets')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'folders') and self.folders is not None:
            _dict['folders'] = [x._to_dict() for x in self.folders]
        if hasattr(self, 'objects') and self.objects is not None:
            _dict['objects'] = [x._to_dict() for x in self.objects]
        if hasattr(self,
                   'site_collections') and self.site_collections is not None:
            _dict['site_collections'] = [
                x._to_dict() for x in self.site_collections
            ]
        if hasattr(self, 'urls') and self.urls is not None:
            _dict['urls'] = [x._to_dict() for x in self.urls]
        if hasattr(self, 'buckets') and self.buckets is not None:
            _dict['buckets'] = [x._to_dict() for x in self.buckets]
        if hasattr(self,
                   'crawl_all_buckets') and self.crawl_all_buckets is not None:
            _dict['crawl_all_buckets'] = self.crawl_all_buckets
        return _dict

    def __str__(self):
        """Return a `str` version of this SourceOptions object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SourceOptionsBuckets(object):
    """
    Object defining a cloud object store bucket to crawl.

    :attr str name: The name of the cloud object store bucket to crawl.
    :attr int limit: (optional) The number of documents to crawl from this cloud object
    store bucket. If not specified, all documents in the bucket are crawled.
    """

    def __init__(self, name, limit=None):
        """
        Initialize a SourceOptionsBuckets object.

        :param str name: The name of the cloud object store bucket to crawl.
        :param int limit: (optional) The number of documents to crawl from this cloud
        object store bucket. If not specified, all documents in the bucket are crawled.
        """
        self.name = name
        self.limit = limit

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SourceOptionsBuckets object from a json dictionary."""
        args = {}
        if 'name' in _dict:
            args['name'] = _dict.get('name')
        else:
            raise ValueError(
                'Required property \'name\' not present in SourceOptionsBuckets JSON'
            )
        if 'limit' in _dict:
            args['limit'] = _dict.get('limit')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'name') and self.name is not None:
            _dict['name'] = self.name
        if hasattr(self, 'limit') and self.limit is not None:
            _dict['limit'] = self.limit
        return _dict

    def __str__(self):
        """Return a `str` version of this SourceOptionsBuckets object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SourceOptionsFolder(object):
    """
    Object that defines a box folder to crawl with this configuration.

    :attr str owner_user_id: The Box user ID of the user who owns the folder to crawl.
    :attr str folder_id: The Box folder ID of the folder to crawl.
    :attr int limit: (optional) The maximum number of documents to crawl for this folder.
    By default, all documents in the folder are crawled.
    """

    def __init__(self, owner_user_id, folder_id, limit=None):
        """
        Initialize a SourceOptionsFolder object.

        :param str owner_user_id: The Box user ID of the user who owns the folder to
        crawl.
        :param str folder_id: The Box folder ID of the folder to crawl.
        :param int limit: (optional) The maximum number of documents to crawl for this
        folder. By default, all documents in the folder are crawled.
        """
        self.owner_user_id = owner_user_id
        self.folder_id = folder_id
        self.limit = limit

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SourceOptionsFolder object from a json dictionary."""
        args = {}
        if 'owner_user_id' in _dict:
            args['owner_user_id'] = _dict.get('owner_user_id')
        else:
            raise ValueError(
                'Required property \'owner_user_id\' not present in SourceOptionsFolder JSON'
            )
        if 'folder_id' in _dict:
            args['folder_id'] = _dict.get('folder_id')
        else:
            raise ValueError(
                'Required property \'folder_id\' not present in SourceOptionsFolder JSON'
            )
        if 'limit' in _dict:
            args['limit'] = _dict.get('limit')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'owner_user_id') and self.owner_user_id is not None:
            _dict['owner_user_id'] = self.owner_user_id
        if hasattr(self, 'folder_id') and self.folder_id is not None:
            _dict['folder_id'] = self.folder_id
        if hasattr(self, 'limit') and self.limit is not None:
            _dict['limit'] = self.limit
        return _dict

    def __str__(self):
        """Return a `str` version of this SourceOptionsFolder object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SourceOptionsObject(object):
    """
    Object that defines a Salesforce document object type crawl with this configuration.

    :attr str name: The name of the Salesforce document object to crawl. For example,
    `case`.
    :attr int limit: (optional) The maximum number of documents to crawl for this document
    object. By default, all documents in the document object are crawled.
    """

    def __init__(self, name, limit=None):
        """
        Initialize a SourceOptionsObject object.

        :param str name: The name of the Salesforce document object to crawl. For example,
        `case`.
        :param int limit: (optional) The maximum number of documents to crawl for this
        document object. By default, all documents in the document object are crawled.
        """
        self.name = name
        self.limit = limit

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SourceOptionsObject object from a json dictionary."""
        args = {}
        if 'name' in _dict:
            args['name'] = _dict.get('name')
        else:
            raise ValueError(
                'Required property \'name\' not present in SourceOptionsObject JSON'
            )
        if 'limit' in _dict:
            args['limit'] = _dict.get('limit')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'name') and self.name is not None:
            _dict['name'] = self.name
        if hasattr(self, 'limit') and self.limit is not None:
            _dict['limit'] = self.limit
        return _dict

    def __str__(self):
        """Return a `str` version of this SourceOptionsObject object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SourceOptionsSiteColl(object):
    """
    Object that defines a Microsoft SharePoint site collection to crawl with this
    configuration.

    :attr str site_collection_path: The Microsoft SharePoint Online site collection path
    to crawl. The path must be be relative to the **organization_url** that was specified
    in the credentials associated with this source configuration.
    :attr int limit: (optional) The maximum number of documents to crawl for this site
    collection. By default, all documents in the site collection are crawled.
    """

    def __init__(self, site_collection_path, limit=None):
        """
        Initialize a SourceOptionsSiteColl object.

        :param str site_collection_path: The Microsoft SharePoint Online site collection
        path to crawl. The path must be be relative to the **organization_url** that was
        specified in the credentials associated with this source configuration.
        :param int limit: (optional) The maximum number of documents to crawl for this
        site collection. By default, all documents in the site collection are crawled.
        """
        self.site_collection_path = site_collection_path
        self.limit = limit

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SourceOptionsSiteColl object from a json dictionary."""
        args = {}
        if 'site_collection_path' in _dict:
            args['site_collection_path'] = _dict.get('site_collection_path')
        else:
            raise ValueError(
                'Required property \'site_collection_path\' not present in SourceOptionsSiteColl JSON'
            )
        if 'limit' in _dict:
            args['limit'] = _dict.get('limit')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'site_collection_path'
                  ) and self.site_collection_path is not None:
            _dict['site_collection_path'] = self.site_collection_path
        if hasattr(self, 'limit') and self.limit is not None:
            _dict['limit'] = self.limit
        return _dict

    def __str__(self):
        """Return a `str` version of this SourceOptionsSiteColl object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SourceOptionsWebCrawl(object):
    """
    Object defining which URL to crawl and how to crawl it.

    :attr str url: The starting URL to crawl.
    :attr bool limit_to_starting_hosts: (optional) When `true`, crawls of the specified
    URL are limited to the host part of the **url** field.
    :attr str crawl_speed: (optional) The number of concurrent URLs to fetch. `gentle`
    means one URL is fetched at a time with a delay between each call. `normal` means as
    many as two URLs are fectched concurrently with a short delay between fetch calls.
    `aggressive` means that up to ten URLs are fetched concurrently with a short delay
    between fetch calls.
    :attr bool allow_untrusted_certificate: (optional) When `true`, allows the crawl to
    interact with HTTPS sites with SSL certificates with untrusted signers.
    :attr int maximum_hops: (optional) The maximum number of hops to make from the initial
    URL. When a page is crawled each link on that page will also be crawled if it is
    within the **maximum_hops** from the initial URL. The first page crawled is 0 hops,
    each link crawled from the first page is 1 hop, each link crawled from those pages is
    2 hops, and so on.
    :attr int request_timeout: (optional) The maximum milliseconds to wait for a response
    from the web server.
    :attr bool override_robots_txt: (optional) When `true`, the crawler will ignore any
    `robots.txt` encountered by the crawler. This should only ever be done when crawling a
    web site the user owns. This must be be set to `true` when a **gateway_id** is specied
    in the **credentials**.
    """

    def __init__(self,
                 url,
                 limit_to_starting_hosts=None,
                 crawl_speed=None,
                 allow_untrusted_certificate=None,
                 maximum_hops=None,
                 request_timeout=None,
                 override_robots_txt=None):
        """
        Initialize a SourceOptionsWebCrawl object.

        :param str url: The starting URL to crawl.
        :param bool limit_to_starting_hosts: (optional) When `true`, crawls of the
        specified URL are limited to the host part of the **url** field.
        :param str crawl_speed: (optional) The number of concurrent URLs to fetch.
        `gentle` means one URL is fetched at a time with a delay between each call.
        `normal` means as many as two URLs are fectched concurrently with a short delay
        between fetch calls. `aggressive` means that up to ten URLs are fetched
        concurrently with a short delay between fetch calls.
        :param bool allow_untrusted_certificate: (optional) When `true`, allows the crawl
        to interact with HTTPS sites with SSL certificates with untrusted signers.
        :param int maximum_hops: (optional) The maximum number of hops to make from the
        initial URL. When a page is crawled each link on that page will also be crawled if
        it is within the **maximum_hops** from the initial URL. The first page crawled is
        0 hops, each link crawled from the first page is 1 hop, each link crawled from
        those pages is 2 hops, and so on.
        :param int request_timeout: (optional) The maximum milliseconds to wait for a
        response from the web server.
        :param bool override_robots_txt: (optional) When `true`, the crawler will ignore
        any `robots.txt` encountered by the crawler. This should only ever be done when
        crawling a web site the user owns. This must be be set to `true` when a
        **gateway_id** is specied in the **credentials**.
        """
        self.url = url
        self.limit_to_starting_hosts = limit_to_starting_hosts
        self.crawl_speed = crawl_speed
        self.allow_untrusted_certificate = allow_untrusted_certificate
        self.maximum_hops = maximum_hops
        self.request_timeout = request_timeout
        self.override_robots_txt = override_robots_txt

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SourceOptionsWebCrawl object from a json dictionary."""
        args = {}
        if 'url' in _dict:
            args['url'] = _dict.get('url')
        else:
            raise ValueError(
                'Required property \'url\' not present in SourceOptionsWebCrawl JSON'
            )
        if 'limit_to_starting_hosts' in _dict:
            args['limit_to_starting_hosts'] = _dict.get(
                'limit_to_starting_hosts')
        if 'crawl_speed' in _dict:
            args['crawl_speed'] = _dict.get('crawl_speed')
        if 'allow_untrusted_certificate' in _dict:
            args['allow_untrusted_certificate'] = _dict.get(
                'allow_untrusted_certificate')
        if 'maximum_hops' in _dict:
            args['maximum_hops'] = _dict.get('maximum_hops')
        if 'request_timeout' in _dict:
            args['request_timeout'] = _dict.get('request_timeout')
        if 'override_robots_txt' in _dict:
            args['override_robots_txt'] = _dict.get('override_robots_txt')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'url') and self.url is not None:
            _dict['url'] = self.url
        if hasattr(self, 'limit_to_starting_hosts'
                  ) and self.limit_to_starting_hosts is not None:
            _dict['limit_to_starting_hosts'] = self.limit_to_starting_hosts
        if hasattr(self, 'crawl_speed') and self.crawl_speed is not None:
            _dict['crawl_speed'] = self.crawl_speed
        if hasattr(self, 'allow_untrusted_certificate'
                  ) and self.allow_untrusted_certificate is not None:
            _dict[
                'allow_untrusted_certificate'] = self.allow_untrusted_certificate
        if hasattr(self, 'maximum_hops') and self.maximum_hops is not None:
            _dict['maximum_hops'] = self.maximum_hops
        if hasattr(self,
                   'request_timeout') and self.request_timeout is not None:
            _dict['request_timeout'] = self.request_timeout
        if hasattr(
                self,
                'override_robots_txt') and self.override_robots_txt is not None:
            _dict['override_robots_txt'] = self.override_robots_txt
        return _dict

    def __str__(self):
        """Return a `str` version of this SourceOptionsWebCrawl object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SourceSchedule(object):
    """
    Object containing the schedule information for the source.

    :attr bool enabled: (optional) When `true`, the source is re-crawled based on the
    **frequency** field in this object. When `false` the source is not re-crawled; When
    `false` and connecting to Salesforce the source is crawled annually.
    :attr str time_zone: (optional) The time zone to base source crawl times on. Possible
    values correspond to the IANA (Internet Assigned Numbers Authority) time zones list.
    :attr str frequency: (optional) The crawl schedule in the specified **time_zone**.
    -  `daily`: Runs every day between 00:00 and 06:00.
    -  `weekly`: Runs every week on Sunday between 00:00 and 06:00.
    -  `monthly`: Runs the on the first Sunday of every month between 00:00 and 06:00.
    """

    def __init__(self, enabled=None, time_zone=None, frequency=None):
        """
        Initialize a SourceSchedule object.

        :param bool enabled: (optional) When `true`, the source is re-crawled based on the
        **frequency** field in this object. When `false` the source is not re-crawled;
        When `false` and connecting to Salesforce the source is crawled annually.
        :param str time_zone: (optional) The time zone to base source crawl times on.
        Possible values correspond to the IANA (Internet Assigned Numbers Authority) time
        zones list.
        :param str frequency: (optional) The crawl schedule in the specified
        **time_zone**.
        -  `daily`: Runs every day between 00:00 and 06:00.
        -  `weekly`: Runs every week on Sunday between 00:00 and 06:00.
        -  `monthly`: Runs the on the first Sunday of every month between 00:00 and 06:00.
        """
        self.enabled = enabled
        self.time_zone = time_zone
        self.frequency = frequency

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SourceSchedule object from a json dictionary."""
        args = {}
        if 'enabled' in _dict:
            args['enabled'] = _dict.get('enabled')
        if 'time_zone' in _dict:
            args['time_zone'] = _dict.get('time_zone')
        if 'frequency' in _dict:
            args['frequency'] = _dict.get('frequency')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'enabled') and self.enabled is not None:
            _dict['enabled'] = self.enabled
        if hasattr(self, 'time_zone') and self.time_zone is not None:
            _dict['time_zone'] = self.time_zone
        if hasattr(self, 'frequency') and self.frequency is not None:
            _dict['frequency'] = self.frequency
        return _dict

    def __str__(self):
        """Return a `str` version of this SourceSchedule object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SourceStatus(object):
    """
    Object containing source crawl status information.

    :attr str status: (optional) The current status of the source crawl for this
    collection. This field returns `not_configured` if the default configuration for this
    source does not have a **source** object defined.
    -  `running` indicates that a crawl to fetch more documents is in progress.
    -  `complete` indicates that the crawl has completed with no errors.
    -  `queued` indicates that the crawl has been paused by the system and will
    automatically restart when possible.
    :attr datetime last_updated: (optional) Date in UTC format indicating when the last
    crawl was attempted. If `null`, no crawl was completed.
    """

    def __init__(self, status=None, last_updated=None):
        """
        Initialize a SourceStatus object.

        :param str status: (optional) The current status of the source crawl for this
        collection. This field returns `not_configured` if the default configuration for
        this source does not have a **source** object defined.
        -  `running` indicates that a crawl to fetch more documents is in progress.
        -  `complete` indicates that the crawl has completed with no errors.
        -  `queued` indicates that the crawl has been paused by the system and will
        automatically restart when possible.
        :param datetime last_updated: (optional) Date in UTC format indicating when the
        last crawl was attempted. If `null`, no crawl was completed.
        """
        self.status = status
        self.last_updated = last_updated

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SourceStatus object from a json dictionary."""
        args = {}
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        if 'last_updated' in _dict:
            args['last_updated'] = string_to_datetime(_dict.get('last_updated'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        if hasattr(self, 'last_updated') and self.last_updated is not None:
            _dict['last_updated'] = datetime_to_string(self.last_updated)
        return _dict

    def __str__(self):
        """Return a `str` version of this SourceStatus object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Term(object):
    """
    Term.

    :attr str field: (optional) The field where the aggregation is located in the
    document.
    :attr int count: (optional)
    """

    def __init__(self,
                 type=None,
                 results=None,
                 matching_results=None,
                 aggregations=None,
                 field=None,
                 count=None):
        """
        Initialize a Term object.

        :param str type: (optional) The type of aggregation command used. For example:
        term, filter, max, min, etc.
        :param list[AggregationResult] results: (optional) Array of aggregation results.
        :param int matching_results: (optional) Number of matching results.
        :param list[QueryAggregation] aggregations: (optional) Aggregations returned by
        the Discovery service.
        :param str field: (optional) The field where the aggregation is located in the
        document.
        :param int count: (optional)
        """
        self.field = field
        self.count = count

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Term object from a json dictionary."""
        args = {}
        if 'field' in _dict:
            args['field'] = _dict.get('field')
        if 'count' in _dict:
            args['count'] = _dict.get('count')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'field') and self.field is not None:
            _dict['field'] = self.field
        if hasattr(self, 'count') and self.count is not None:
            _dict['count'] = self.count
        return _dict

    def __str__(self):
        """Return a `str` version of this Term object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class TestDocument(object):
    """
    TestDocument.

    :attr str configuration_id: (optional) The unique identifier for the configuration.
    :attr str status: (optional) Status of the preview operation.
    :attr int enriched_field_units: (optional) The number of 10-kB chunks of field data
    that were enriched. This can be used to estimate the cost of running a real ingestion.
    :attr str original_media_type: (optional) Format of the test document.
    :attr list[DocumentSnapshot] snapshots: (optional) An array of objects that describe
    each step in the preview process.
    :attr list[Notice] notices: (optional) An array of notice messages about the preview
    operation.
    """

    def __init__(self,
                 configuration_id=None,
                 status=None,
                 enriched_field_units=None,
                 original_media_type=None,
                 snapshots=None,
                 notices=None):
        """
        Initialize a TestDocument object.

        :param str configuration_id: (optional) The unique identifier for the
        configuration.
        :param str status: (optional) Status of the preview operation.
        :param int enriched_field_units: (optional) The number of 10-kB chunks of field
        data that were enriched. This can be used to estimate the cost of running a real
        ingestion.
        :param str original_media_type: (optional) Format of the test document.
        :param list[DocumentSnapshot] snapshots: (optional) An array of objects that
        describe each step in the preview process.
        :param list[Notice] notices: (optional) An array of notice messages about the
        preview operation.
        """
        self.configuration_id = configuration_id
        self.status = status
        self.enriched_field_units = enriched_field_units
        self.original_media_type = original_media_type
        self.snapshots = snapshots
        self.notices = notices

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a TestDocument object from a json dictionary."""
        args = {}
        if 'configuration_id' in _dict:
            args['configuration_id'] = _dict.get('configuration_id')
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        if 'enriched_field_units' in _dict:
            args['enriched_field_units'] = _dict.get('enriched_field_units')
        if 'original_media_type' in _dict:
            args['original_media_type'] = _dict.get('original_media_type')
        if 'snapshots' in _dict:
            args['snapshots'] = [
                DocumentSnapshot._from_dict(x) for x in (_dict.get('snapshots'))
            ]
        if 'notices' in _dict:
            args['notices'] = [
                Notice._from_dict(x) for x in (_dict.get('notices'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self,
                   'configuration_id') and self.configuration_id is not None:
            _dict['configuration_id'] = self.configuration_id
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        if hasattr(self, 'enriched_field_units'
                  ) and self.enriched_field_units is not None:
            _dict['enriched_field_units'] = self.enriched_field_units
        if hasattr(
                self,
                'original_media_type') and self.original_media_type is not None:
            _dict['original_media_type'] = self.original_media_type
        if hasattr(self, 'snapshots') and self.snapshots is not None:
            _dict['snapshots'] = [x._to_dict() for x in self.snapshots]
        if hasattr(self, 'notices') and self.notices is not None:
            _dict['notices'] = [x._to_dict() for x in self.notices]
        return _dict

    def __str__(self):
        """Return a `str` version of this TestDocument object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class Timeslice(object):
    """
    Timeslice.

    :attr str field: (optional) The field where the aggregation is located in the
    document.
    :attr str interval: (optional) Interval of the aggregation. Valid date interval values
    are second/seconds minute/minutes, hour/hours, day/days, week/weeks, month/months, and
    year/years.
    :attr bool anomaly: (optional) Used to indicate that anomaly detection should be
    performed. Anomaly detection is used to locate unusual datapoints within a time
    series.
    """

    def __init__(self,
                 type=None,
                 results=None,
                 matching_results=None,
                 aggregations=None,
                 field=None,
                 interval=None,
                 anomaly=None):
        """
        Initialize a Timeslice object.

        :param str type: (optional) The type of aggregation command used. For example:
        term, filter, max, min, etc.
        :param list[AggregationResult] results: (optional) Array of aggregation results.
        :param int matching_results: (optional) Number of matching results.
        :param list[QueryAggregation] aggregations: (optional) Aggregations returned by
        the Discovery service.
        :param str field: (optional) The field where the aggregation is located in the
        document.
        :param str interval: (optional) Interval of the aggregation. Valid date interval
        values are second/seconds minute/minutes, hour/hours, day/days, week/weeks,
        month/months, and year/years.
        :param bool anomaly: (optional) Used to indicate that anomaly detection should be
        performed. Anomaly detection is used to locate unusual datapoints within a time
        series.
        """
        self.field = field
        self.interval = interval
        self.anomaly = anomaly

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a Timeslice object from a json dictionary."""
        args = {}
        if 'field' in _dict:
            args['field'] = _dict.get('field')
        if 'interval' in _dict:
            args['interval'] = _dict.get('interval')
        if 'anomaly' in _dict:
            args['anomaly'] = _dict.get('anomaly')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'field') and self.field is not None:
            _dict['field'] = self.field
        if hasattr(self, 'interval') and self.interval is not None:
            _dict['interval'] = self.interval
        if hasattr(self, 'anomaly') and self.anomaly is not None:
            _dict['anomaly'] = self.anomaly
        return _dict

    def __str__(self):
        """Return a `str` version of this Timeslice object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class TokenDictRule(object):
    """
    An object defining a single tokenizaion rule.

    :attr str text: The string to tokenize.
    :attr list[str] tokens: Array of tokens that the `text` field is split into when
    found.
    :attr list[str] readings: (optional) Array of tokens that represent the content of the
    `text` field in an alternate character set.
    :attr str part_of_speech: The part of speech that the `text` string belongs to. For
    example `noun`. Custom parts of speech can be specified.
    """

    def __init__(self, text, tokens, part_of_speech, readings=None):
        """
        Initialize a TokenDictRule object.

        :param str text: The string to tokenize.
        :param list[str] tokens: Array of tokens that the `text` field is split into when
        found.
        :param str part_of_speech: The part of speech that the `text` string belongs to.
        For example `noun`. Custom parts of speech can be specified.
        :param list[str] readings: (optional) Array of tokens that represent the content
        of the `text` field in an alternate character set.
        """
        self.text = text
        self.tokens = tokens
        self.readings = readings
        self.part_of_speech = part_of_speech

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a TokenDictRule object from a json dictionary."""
        args = {}
        if 'text' in _dict:
            args['text'] = _dict.get('text')
        else:
            raise ValueError(
                'Required property \'text\' not present in TokenDictRule JSON')
        if 'tokens' in _dict:
            args['tokens'] = _dict.get('tokens')
        else:
            raise ValueError(
                'Required property \'tokens\' not present in TokenDictRule JSON'
            )
        if 'readings' in _dict:
            args['readings'] = _dict.get('readings')
        if 'part_of_speech' in _dict:
            args['part_of_speech'] = _dict.get('part_of_speech')
        else:
            raise ValueError(
                'Required property \'part_of_speech\' not present in TokenDictRule JSON'
            )
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'text') and self.text is not None:
            _dict['text'] = self.text
        if hasattr(self, 'tokens') and self.tokens is not None:
            _dict['tokens'] = self.tokens
        if hasattr(self, 'readings') and self.readings is not None:
            _dict['readings'] = self.readings
        if hasattr(self, 'part_of_speech') and self.part_of_speech is not None:
            _dict['part_of_speech'] = self.part_of_speech
        return _dict

    def __str__(self):
        """Return a `str` version of this TokenDictRule object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class TokenDictStatusResponse(object):
    """
    Object describing the current status of the wordlist.

    :attr str status: (optional) Current wordlist status for the specified collection.
    :attr str type: (optional) The type for this wordlist. Can be
    `tokenization_dictionary` or `stopwords`.
    """

    def __init__(self, status=None, type=None):
        """
        Initialize a TokenDictStatusResponse object.

        :param str status: (optional) Current wordlist status for the specified
        collection.
        :param str type: (optional) The type for this wordlist. Can be
        `tokenization_dictionary` or `stopwords`.
        """
        self.status = status
        self.type = type

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a TokenDictStatusResponse object from a json dictionary."""
        args = {}
        if 'status' in _dict:
            args['status'] = _dict.get('status')
        if 'type' in _dict:
            args['type'] = _dict.get('type')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'status') and self.status is not None:
            _dict['status'] = self.status
        if hasattr(self, 'type') and self.type is not None:
            _dict['type'] = self.type
        return _dict

    def __str__(self):
        """Return a `str` version of this TokenDictStatusResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class TopHits(object):
    """
    TopHits.

    :attr int size: (optional) Number of top hits returned by the aggregation.
    :attr TopHitsResults hits: (optional)
    """

    def __init__(self,
                 type=None,
                 results=None,
                 matching_results=None,
                 aggregations=None,
                 size=None,
                 hits=None):
        """
        Initialize a TopHits object.

        :param str type: (optional) The type of aggregation command used. For example:
        term, filter, max, min, etc.
        :param list[AggregationResult] results: (optional) Array of aggregation results.
        :param int matching_results: (optional) Number of matching results.
        :param list[QueryAggregation] aggregations: (optional) Aggregations returned by
        the Discovery service.
        :param int size: (optional) Number of top hits returned by the aggregation.
        :param TopHitsResults hits: (optional)
        """
        self.size = size
        self.hits = hits

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a TopHits object from a json dictionary."""
        args = {}
        if 'size' in _dict:
            args['size'] = _dict.get('size')
        if 'hits' in _dict:
            args['hits'] = TopHitsResults._from_dict(_dict.get('hits'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'size') and self.size is not None:
            _dict['size'] = self.size
        if hasattr(self, 'hits') and self.hits is not None:
            _dict['hits'] = self.hits._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this TopHits object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class TopHitsResults(object):
    """
    TopHitsResults.

    :attr int matching_results: (optional) Number of matching results.
    :attr list[QueryResult] hits: (optional) Top results returned by the aggregation.
    """

    def __init__(self, matching_results=None, hits=None):
        """
        Initialize a TopHitsResults object.

        :param int matching_results: (optional) Number of matching results.
        :param list[QueryResult] hits: (optional) Top results returned by the aggregation.
        """
        self.matching_results = matching_results
        self.hits = hits

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a TopHitsResults object from a json dictionary."""
        args = {}
        if 'matching_results' in _dict:
            args['matching_results'] = _dict.get('matching_results')
        if 'hits' in _dict:
            args['hits'] = [
                QueryResult._from_dict(x) for x in (_dict.get('hits'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self,
                   'matching_results') and self.matching_results is not None:
            _dict['matching_results'] = self.matching_results
        if hasattr(self, 'hits') and self.hits is not None:
            _dict['hits'] = [x._to_dict() for x in self.hits]
        return _dict

    def __str__(self):
        """Return a `str` version of this TopHitsResults object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class TrainingDataSet(object):
    """
    TrainingDataSet.

    :attr str environment_id: (optional) The environment id associated with this training
    data set.
    :attr str collection_id: (optional) The collection id associated with this training
    data set.
    :attr list[TrainingQuery] queries: (optional) Array of training queries.
    """

    def __init__(self, environment_id=None, collection_id=None, queries=None):
        """
        Initialize a TrainingDataSet object.

        :param str environment_id: (optional) The environment id associated with this
        training data set.
        :param str collection_id: (optional) The collection id associated with this
        training data set.
        :param list[TrainingQuery] queries: (optional) Array of training queries.
        """
        self.environment_id = environment_id
        self.collection_id = collection_id
        self.queries = queries

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a TrainingDataSet object from a json dictionary."""
        args = {}
        if 'environment_id' in _dict:
            args['environment_id'] = _dict.get('environment_id')
        if 'collection_id' in _dict:
            args['collection_id'] = _dict.get('collection_id')
        if 'queries' in _dict:
            args['queries'] = [
                TrainingQuery._from_dict(x) for x in (_dict.get('queries'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'environment_id') and self.environment_id is not None:
            _dict['environment_id'] = self.environment_id
        if hasattr(self, 'collection_id') and self.collection_id is not None:
            _dict['collection_id'] = self.collection_id
        if hasattr(self, 'queries') and self.queries is not None:
            _dict['queries'] = [x._to_dict() for x in self.queries]
        return _dict

    def __str__(self):
        """Return a `str` version of this TrainingDataSet object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class TrainingExample(object):
    """
    TrainingExample.

    :attr str document_id: (optional) The document ID associated with this training
    example.
    :attr str cross_reference: (optional) The cross reference associated with this
    training example.
    :attr int relevance: (optional) The relevance of the training example.
    """

    def __init__(self, document_id=None, cross_reference=None, relevance=None):
        """
        Initialize a TrainingExample object.

        :param str document_id: (optional) The document ID associated with this training
        example.
        :param str cross_reference: (optional) The cross reference associated with this
        training example.
        :param int relevance: (optional) The relevance of the training example.
        """
        self.document_id = document_id
        self.cross_reference = cross_reference
        self.relevance = relevance

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a TrainingExample object from a json dictionary."""
        args = {}
        if 'document_id' in _dict:
            args['document_id'] = _dict.get('document_id')
        if 'cross_reference' in _dict:
            args['cross_reference'] = _dict.get('cross_reference')
        if 'relevance' in _dict:
            args['relevance'] = _dict.get('relevance')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'document_id') and self.document_id is not None:
            _dict['document_id'] = self.document_id
        if hasattr(self,
                   'cross_reference') and self.cross_reference is not None:
            _dict['cross_reference'] = self.cross_reference
        if hasattr(self, 'relevance') and self.relevance is not None:
            _dict['relevance'] = self.relevance
        return _dict

    def __str__(self):
        """Return a `str` version of this TrainingExample object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class TrainingExampleList(object):
    """
    TrainingExampleList.

    :attr list[TrainingExample] examples: (optional) Array of training examples.
    """

    def __init__(self, examples=None):
        """
        Initialize a TrainingExampleList object.

        :param list[TrainingExample] examples: (optional) Array of training examples.
        """
        self.examples = examples

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a TrainingExampleList object from a json dictionary."""
        args = {}
        if 'examples' in _dict:
            args['examples'] = [
                TrainingExample._from_dict(x) for x in (_dict.get('examples'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'examples') and self.examples is not None:
            _dict['examples'] = [x._to_dict() for x in self.examples]
        return _dict

    def __str__(self):
        """Return a `str` version of this TrainingExampleList object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class TrainingQuery(object):
    """
    TrainingQuery.

    :attr str query_id: (optional) The query ID associated with the training query.
    :attr str natural_language_query: (optional) The natural text query for the training
    query.
    :attr str filter: (optional) The filter used on the collection before the
    **natural_language_query** is applied.
    :attr list[TrainingExample] examples: (optional) Array of training examples.
    """

    def __init__(self,
                 query_id=None,
                 natural_language_query=None,
                 filter=None,
                 examples=None):
        """
        Initialize a TrainingQuery object.

        :param str query_id: (optional) The query ID associated with the training query.
        :param str natural_language_query: (optional) The natural text query for the
        training query.
        :param str filter: (optional) The filter used on the collection before the
        **natural_language_query** is applied.
        :param list[TrainingExample] examples: (optional) Array of training examples.
        """
        self.query_id = query_id
        self.natural_language_query = natural_language_query
        self.filter = filter
        self.examples = examples

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a TrainingQuery object from a json dictionary."""
        args = {}
        if 'query_id' in _dict:
            args['query_id'] = _dict.get('query_id')
        if 'natural_language_query' in _dict:
            args['natural_language_query'] = _dict.get('natural_language_query')
        if 'filter' in _dict:
            args['filter'] = _dict.get('filter')
        if 'examples' in _dict:
            args['examples'] = [
                TrainingExample._from_dict(x) for x in (_dict.get('examples'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'query_id') and self.query_id is not None:
            _dict['query_id'] = self.query_id
        if hasattr(self, 'natural_language_query'
                  ) and self.natural_language_query is not None:
            _dict['natural_language_query'] = self.natural_language_query
        if hasattr(self, 'filter') and self.filter is not None:
            _dict['filter'] = self.filter
        if hasattr(self, 'examples') and self.examples is not None:
            _dict['examples'] = [x._to_dict() for x in self.examples]
        return _dict

    def __str__(self):
        """Return a `str` version of this TrainingQuery object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class TrainingStatus(object):
    """
    TrainingStatus.

    :attr int total_examples: (optional) The total number of training examples uploaded to
    this collection.
    :attr bool available: (optional) When `true`, the collection has been successfully
    trained.
    :attr bool processing: (optional) When `true`, the collection is currently processing
    training.
    :attr bool minimum_queries_added: (optional) When `true`, the collection has a
    sufficent amount of queries added for training to occur.
    :attr bool minimum_examples_added: (optional) When `true`, the collection has a
    sufficent amount of examples added for training to occur.
    :attr bool sufficient_label_diversity: (optional) When `true`, the collection has a
    sufficent amount of diversity in labeled results for training to occur.
    :attr int notices: (optional) The number of notices associated with this data set.
    :attr datetime successfully_trained: (optional) The timestamp of when the collection
    was successfully trained.
    :attr datetime data_updated: (optional) The timestamp of when the data was uploaded.
    """

    def __init__(self,
                 total_examples=None,
                 available=None,
                 processing=None,
                 minimum_queries_added=None,
                 minimum_examples_added=None,
                 sufficient_label_diversity=None,
                 notices=None,
                 successfully_trained=None,
                 data_updated=None):
        """
        Initialize a TrainingStatus object.

        :param int total_examples: (optional) The total number of training examples
        uploaded to this collection.
        :param bool available: (optional) When `true`, the collection has been
        successfully trained.
        :param bool processing: (optional) When `true`, the collection is currently
        processing training.
        :param bool minimum_queries_added: (optional) When `true`, the collection has a
        sufficent amount of queries added for training to occur.
        :param bool minimum_examples_added: (optional) When `true`, the collection has a
        sufficent amount of examples added for training to occur.
        :param bool sufficient_label_diversity: (optional) When `true`, the collection has
        a sufficent amount of diversity in labeled results for training to occur.
        :param int notices: (optional) The number of notices associated with this data
        set.
        :param datetime successfully_trained: (optional) The timestamp of when the
        collection was successfully trained.
        :param datetime data_updated: (optional) The timestamp of when the data was
        uploaded.
        """
        self.total_examples = total_examples
        self.available = available
        self.processing = processing
        self.minimum_queries_added = minimum_queries_added
        self.minimum_examples_added = minimum_examples_added
        self.sufficient_label_diversity = sufficient_label_diversity
        self.notices = notices
        self.successfully_trained = successfully_trained
        self.data_updated = data_updated

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a TrainingStatus object from a json dictionary."""
        args = {}
        if 'total_examples' in _dict:
            args['total_examples'] = _dict.get('total_examples')
        if 'available' in _dict:
            args['available'] = _dict.get('available')
        if 'processing' in _dict:
            args['processing'] = _dict.get('processing')
        if 'minimum_queries_added' in _dict:
            args['minimum_queries_added'] = _dict.get('minimum_queries_added')
        if 'minimum_examples_added' in _dict:
            args['minimum_examples_added'] = _dict.get('minimum_examples_added')
        if 'sufficient_label_diversity' in _dict:
            args['sufficient_label_diversity'] = _dict.get(
                'sufficient_label_diversity')
        if 'notices' in _dict:
            args['notices'] = _dict.get('notices')
        if 'successfully_trained' in _dict:
            args['successfully_trained'] = string_to_datetime(
                _dict.get('successfully_trained'))
        if 'data_updated' in _dict:
            args['data_updated'] = string_to_datetime(_dict.get('data_updated'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'total_examples') and self.total_examples is not None:
            _dict['total_examples'] = self.total_examples
        if hasattr(self, 'available') and self.available is not None:
            _dict['available'] = self.available
        if hasattr(self, 'processing') and self.processing is not None:
            _dict['processing'] = self.processing
        if hasattr(self, 'minimum_queries_added'
                  ) and self.minimum_queries_added is not None:
            _dict['minimum_queries_added'] = self.minimum_queries_added
        if hasattr(self, 'minimum_examples_added'
                  ) and self.minimum_examples_added is not None:
            _dict['minimum_examples_added'] = self.minimum_examples_added
        if hasattr(self, 'sufficient_label_diversity'
                  ) and self.sufficient_label_diversity is not None:
            _dict[
                'sufficient_label_diversity'] = self.sufficient_label_diversity
        if hasattr(self, 'notices') and self.notices is not None:
            _dict['notices'] = self.notices
        if hasattr(self, 'successfully_trained'
                  ) and self.successfully_trained is not None:
            _dict['successfully_trained'] = datetime_to_string(
                self.successfully_trained)
        if hasattr(self, 'data_updated') and self.data_updated is not None:
            _dict['data_updated'] = datetime_to_string(self.data_updated)
        return _dict

    def __str__(self):
        """Return a `str` version of this TrainingStatus object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class WordHeadingDetection(object):
    """
    WordHeadingDetection.

    :attr list[FontSetting] fonts: (optional)
    :attr list[WordStyle] styles: (optional)
    """

    def __init__(self, fonts=None, styles=None):
        """
        Initialize a WordHeadingDetection object.

        :param list[FontSetting] fonts: (optional)
        :param list[WordStyle] styles: (optional)
        """
        self.fonts = fonts
        self.styles = styles

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a WordHeadingDetection object from a json dictionary."""
        args = {}
        if 'fonts' in _dict:
            args['fonts'] = [
                FontSetting._from_dict(x) for x in (_dict.get('fonts'))
            ]
        if 'styles' in _dict:
            args['styles'] = [
                WordStyle._from_dict(x) for x in (_dict.get('styles'))
            ]
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'fonts') and self.fonts is not None:
            _dict['fonts'] = [x._to_dict() for x in self.fonts]
        if hasattr(self, 'styles') and self.styles is not None:
            _dict['styles'] = [x._to_dict() for x in self.styles]
        return _dict

    def __str__(self):
        """Return a `str` version of this WordHeadingDetection object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class WordSettings(object):
    """
    A list of Word conversion settings.

    :attr WordHeadingDetection heading: (optional)
    """

    def __init__(self, heading=None):
        """
        Initialize a WordSettings object.

        :param WordHeadingDetection heading: (optional)
        """
        self.heading = heading

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a WordSettings object from a json dictionary."""
        args = {}
        if 'heading' in _dict:
            args['heading'] = WordHeadingDetection._from_dict(
                _dict.get('heading'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'heading') and self.heading is not None:
            _dict['heading'] = self.heading._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this WordSettings object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class WordStyle(object):
    """
    WordStyle.

    :attr int level: (optional) HTML head level that content matching this style is tagged
    with.
    :attr list[str] names: (optional) Array of word style names to convert.
    """

    def __init__(self, level=None, names=None):
        """
        Initialize a WordStyle object.

        :param int level: (optional) HTML head level that content matching this style is
        tagged with.
        :param list[str] names: (optional) Array of word style names to convert.
        """
        self.level = level
        self.names = names

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a WordStyle object from a json dictionary."""
        args = {}
        if 'level' in _dict:
            args['level'] = _dict.get('level')
        if 'names' in _dict:
            args['names'] = _dict.get('names')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'level') and self.level is not None:
            _dict['level'] = self.level
        if hasattr(self, 'names') and self.names is not None:
            _dict['names'] = self.names
        return _dict

    def __str__(self):
        """Return a `str` version of this WordStyle object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class XPathPatterns(object):
    """
    XPathPatterns.

    :attr list[str] xpaths: (optional) An array to XPaths.
    """

    def __init__(self, xpaths=None):
        """
        Initialize a XPathPatterns object.

        :param list[str] xpaths: (optional) An array to XPaths.
        """
        self.xpaths = xpaths

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a XPathPatterns object from a json dictionary."""
        args = {}
        if 'xpaths' in _dict:
            args['xpaths'] = _dict.get('xpaths')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'xpaths') and self.xpaths is not None:
            _dict['xpaths'] = self.xpaths
        return _dict

    def __str__(self):
        """Return a `str` version of this XPathPatterns object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """Return `true` when self and other are equal, false otherwise."""
        if not isinstance(other, self.__class__):
            return False
        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other
